In-house Database Research Articles

A strategy integrating improved mass defect filtering, diagnostic product ions, and molecular network for rapid screening and systematic characterization of steroidal alkaloids in Fritillaria ussuriensis

An ultra-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS) method was employed to efficiently and rapidly analyze the chemical composition of steroidal alkaloids in Fritillaria ussuriensis Maxim (FM). The integration of nitrogen rule and improved mass defect filtering eliminated 84.61% of interfering MS1 peaks and facilitated subtype classification. Subsequently, six diagnostic product ions (DPIs) for Fritillaria alkaloids were summarized, guiding structural identification. Additionally, the adoption of molecular networks to infer potential compounds forms a new four-step comprehensive strategy for systematic screening and identification of Fritillaria alkaloids. By screening with the MDF window constructed from the Fritillaria alkaloids MS database combined with the nitrogen rule, a significant number of interfering MS1 peaks were eliminated, and different subtypes were distinguished. In FM, the number of positive-mode MS1 peaks was reduced by 84.61% (from 8,728 to 1,343). By summarizing the fragmentation behaviors of 22 reference standards, the fragmentation pathways and DPIs of five types of steroidal alkaloids were confirmed, providing the first evidence for DPIs of cevanine-seven-membered type Fritillaria alkaloids. Structural confirmation of MS1 peaks was carried out using an in-house database and DPIs. Furthermore, a feature-based molecular network (FBMN) was employed to cluster similar compounds into network clusters for rapid classification and to infer potential steroidal alkaloids using known compounds. A total of 103 Fritillaria alkaloids (65 cevanine type, 7 cevanine-seven-membered type, 18 jervine type, 5 veratramine type, 5 secosolanidine type, and 3 solanidine type) were identified, including 4 potential new compounds and 20 compounds that have been identified for the first time. This innovative comprehensive strategy, which includes NRF, improved MDF, DPIs, and FBMN, can be applied to rapidly screen, classify components, and conduct comprehensive characterization of complex samples such as herbal medicines.

Comprehensive metabolome characterization of leaves, internodes, and aerial roots of Vanilla planifolia by untargeted LC-MS and GC × GC-MS.

Untargeted metabolomics is a powerful tool that provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites, especially when combining different metabolomic platforms. Vanilla is one of the world's most popular flavors originating from cured pods of the orchid Vanilla planifolia. However, only a few studies have investigated the metabolome of V. planifolia, and no LC-MS or GC-MS metabolomics studies with respect to leaves have been performed. The aim of the study was to comprehensively characterize the metabolome of different organs (leaves, internodes, and aerial roots) of V. planifolia. Characterization of the metabolome was achieved using two complementary platforms (GC × GC-MS, LC-QToF-MS), and metabolite identification was based on a comparison with in-house databases or curated external spectral libraries. In total, 127 metabolites could be identified with high certainty (confidence level 1 or 2) including sugars, amino acids, fatty acids, organic acids, and amines/amides but also secondary metabolites such as vanillin-related metabolites, flavonoids, and terpenoids. Ninty-eight metabolites showed significantly different intensities between the plant organs. Most strikingly, aglycons of flavonoids and vanillin-related metabolites were elevated in aerial roots, whereas its O-glycoside forms tended to be higher in leaves and/or internodes. This suggests that the more bioactive aglycones may accumulate where preferably needed, e.g. for defense against pathogens. The results derived from the study substantially expand the knowledge regarding the vanilla metabolome forming a valuable basis for more targeted investigations in future studies, e.g. towards an optimization of vanilla plant cultivation.

CDH23-Associated Usher Syndrome: Clinical Features, Retinal Imaging, and Natural History.

The purpose of this study was to analyze the clinical spectrum and natural history of CDH23-associated Usher syndrome type ID (USH1D). Molecularly-confirmed individuals had data extracted from medical records. Retinal imaging was extracted from an in-house database. The main outcome measurements were retinal imaging and electroretinography (ERG) and clinical findings, including age of onset, symptoms, best-corrected visual acuity (BCVA), outer nuclear layer (ONL) thickness, ellipsoid zone width (EZW), and hyperautofluorescent ring area. Thirty-one patients were identified, harboring 40 variants in CDH23 (10 being novel). The mean (range, ±SD) age of symptom onset was 10.1years (range = 1-18, SD = ±4.1). The most common visual symptoms at presentation were nyctalopia (93.5%) and peripheral vision difficulties (61.3%). The mean BCVA at baseline was 0.25 ± 0.22 in the right eyes and 0.35 ± 0.58 LogMAR in the left eyes. The mean annual loss rate in BCVA was 0.018 LogMAR/year over a mean follow-up of 9.5years. Individuals harboring the c.5237G>A p.(Arg1746Gln) allele had retinitis pigmentosa (RP) sparing the superior retina. Seventy-seven percent of patients had hyperautofluorescent rings in fundus autofluorescence. Full-field and pattern ERGs indicated moderate-severe rod-cone or photoreceptor dysfunction with relative sparing of macular function in most patients tested. Optical coherence tomography (OCT) revealed intraretinal cysts in the transfoveal B-scan of 13 individuals (43.3%). The rate of EZW and ONL thickness loss was mild and suggestive of a wide window of macular preservation. Despite the early onset of symptoms, USH1D has a slowly progressive phenotype. There is high interocular symmetry across all parameters, making it an attractive target for novel therapies.

Magnetic ligand fishing protocol combined with HPLC-FT-ICR-MS for screening potential α-Glucosidase inhibitors from UCG and in silico analysis

Uremic Clearance Granule (UCG) is a traditional Chinese medicines (TCMs) that has been recognized as potentially effective treatment for diabetic nephropathy (DN). However, the chemical composition and the hypoglycemic ingredients of UCG remain unclear. In this experiment, a magnetic ligand fishing protocol combined with HPLC coupled Fourier transform ion cyclotron resonance mass spectrometry (HPLC-FT-ICR-MS) technology was developed to screen and identify α-Glucosidase inhibitors from UCG. First, constituents of UCG was identified by HPLC-FT-ICR-MS. Next, α-Glucosidase coated Fe3O4@SiO2@NH2 (Fe3O4@SiO2@NH2@α-Glucosidase) nano composites was synthesized. The essential parameters (concentration of Glutaraldehyde (GA), ratio of Fe3O4@SiO2@NH2 to enzyme, crosslinking time and immobilization time) were optimized to obtain maximum enzyme activity and the performance of immobilized enzyme was compared with that of free enzyme. The α-Glucosidase inhibitory activities were then evaluated using autodock and the 4-Nitrophenyl-α-D-glucopyranoside (pNPG) method. As a result, 142 compounds were identified were identified by comparing the retention time, molecular ions and fragmentation behaviors with the reference compounds or the in-house database. 20 possible α-Glucosidase activity inhibitory components were identified using HPLC-FT-ICR-MS. Molecular docking and inhibition studies showed that 4 compuunds including Limonexic acid, Sanggenol A, Glabrone, Matrine were more likely to stronger α-Glucosidase inhibitory activities than acarbose. In conclusion, the proposed approach, which combined highly specific screening with HPLC-FT-ICR-MS, provided a powerful platform for discovering bioactive components from multi-component and multi-target traditional Chinese medicines (TCMs).

P-550 Monoallelic CCNB2 variants may cause oocyte maturation defects and embryo developmental arrest

Abstract Study question Have all the genes that may cause embryo development arrest and oocyte maturation defects been identified in female patients? Summary answer We identified a variant in CCNB2 in our patient. To our knowledge, this is first time that meiotic arrest can be caused by mutated-CCNB2. What is known already Successful reproduction involves the maturation of gametes, fertilization, and early development of the embryo. Oocyte maturation involves a sequence of both morphological and molecular transformations, progressing from germinal vesicle oocytes to metaphase I oocytes and ultimately to metaphase II oocytes. Any disruption in the process of oocyte maturation can result in infertility. With the widespread use of whole exome sequencing (WES), several genes that influence oocyte maturation at different stages have been recently identified. Study design, size, duration We here report the case of repeated ART failure due to oocyte maturation defect and embryo developmental arrest. Participants/materials, setting, methods A 30-year-old female and 38-year-old male applied to our clinic due to unexplained infertility for 4 years. The first ART attempt resulted in 2 of 13 oocytes with late MII. During ART performed in our center, germinal vesicle and meiotic arrest were observed in all oocytes. No mature oocytes were obtained. Her grandfather’s sister was also infertile. WES and Sanger analysis were performed to detect any mutation in known/candidate genes and show familial segregation Main results and the role of chance WES analysis revealed no mutation in genes that were previously reported as a cause of oocyte maturation defect or early embryo development in human. We do a further analysis of genes highly or specifically expressed in oocytes or expressed at low levels yet previous studies have suggested its role in embryo development. We identified a c.787C>T, p.Arg263* heterozygous nonsense variant in the CCNB2 gene that was extremely rare in both multiple databases and our in-house database. Multiple lines of computational evidence support the deleterious effect of the variant on the gene product. This variant was transmitted from her healthy father. CCNNB2 is not expressed in any cells other than oocytes in human. The activity of the M phase-promoting factor (MPF) is crucial for advancing through both mitosis and meiosis. CCNB2 plays a vital role by contributing to the activity of pre-MPF during prophase, necessary for generating enough MPF to proceed through maturation. Furthermore, CCNB2 is significantly involved in mouse oocyte meiosis, playing a key role in both the G2/M and MI/anaphase I transitions. Limitations, reasons for caution New disease-causing variants in this gene should be demonstrated in larger cohorts with female infertility. In addition, further functional studies should be carried out both in CCNB2-mutated human and animals. Wider implications of the findings This study may provide a better understanding background of female infertility and the failure of the ART process. CCNB2 may have a crucial role in the oocyte maturation process and can be utilized as a female infertility genetic marker. Trial registration number NA

Micronutrients in Adverse Pregnancy Outcomes

About 10 to 20% of reported pregnancies have complications like spontaneous abortion (SA), preeclampsia (PE), preterm birth (PTB), and fetal growth restriction (FGR); 60% are attributed to maternal nutritional alterations. Multiple micronutrients (MMN) are supplemented in the antenatal period, but no proper validation/guidelines are available regarding dosing/time, the need for initiation, and the duration of supplementation. Studies have reported adverse pregnancy complications related to the overuse/unwanted use of multiple micronutrient supplementations during pregnancy. Identifying the exact population requiring supplementation is necessary to prevent its abuse. This article attempts to review the impacts of micronutrient deficiency/supplementation in cases of SA, FGR, and gestational diabetes mellitus (GDM), preterm delivery and PE. The study used a literature search using PubMed, Google Scholar, Mendeley, and Scopus Databases using search words pregnancy, spontaneous abortion, gestational diabetes mellitus (GDM), fetal growth restriction (FGR), preterm delivery, preeclampsia (PE) or “adverse pregnancy” associated with minerals, micronutrients, or supplementation. The review also considered in-house literature databases, a single-window search at Kasturba Medical College (KMC) Health sciences library, MAHE (Manipal Academy of Higher Education). The figures included in the study were created by Biorender.com. Micronutrients play multiple roles during pregnancy and fetoplacental growth stimulating growth hormone secretion, Lysyl oxidase (LOX), involved in the crosslinking between collagen and elastin in the amniotic membrane, downregulation of interleukin (IL)-1 alpha, IL-1 beta, IL-4, IL-6, Il-10, IL-12, tumor necrosis factor (TNF)-alpha and several chemokines involved in hypertension, immune-inflammatory pathways, attenuate insulin resistance, structural development of neurons and glia. Over-supplementation has led to complications such as spontaneous abortion and gestational diabetes mellitus. Since there is a lack of standardization concerning micronutrient supplementation during pregnancy, there is a need for systematic study related to the role of micronutrients during each trimester of pregnancy to optimize its supplementation and to prevent hazards associated with its abuse.

ETMR-23. CNS SARCOMAS WITHCIC- ORATXN1-ALTERATIONS — A META-ANALYSIS OF CLINICAL AND MOLECULAR FEATURES IN A LARGE SERIES OF PATIENTS

Abstract BACKGROUND In 2021, the 5th WHO classification of central nervous system (CNS) tumors acknowledged CNS sarcomas with CIC alterations as a distinct tumor type, which may also expand to non-CIC alterations including ATXN1. To tackle the lack of treatment protocols for these highly aggressive tumors, we conducted a meta-analysis to provide an overview of clinical and molecular characteristics, define clinically relevant subtypes, and ultimately advise on treatment guidelines. METHODS We collected molecular and clinical data for >200 patients with CIC- or ATXN1-altered CNS sarcomas by screening our in-house DNA methylation database (581 potential patients initially identified), publication databases (50 patients), and contacting centers worldwide (60 patients). Tumor tissue (FFPE and fresh frozen) for further molecular characterization was obtained from a subset of patients. DNA methylation-based clustering analyses (t-SNE, UMAP, consensus partitioning) were performed, integrating gene fusion details (RNAseq, FISH), copy-number variations, and clinical patient data to identify associations between (epi-)genetic and clinical parameters. RESULTS Most prominent fusion partners for CIC (n=47) and ATXN1 (n=9) were NUTM1 (n=18), LEUTX (n=17) and DUX4 (n=15). Clustering analyses of DNA methylation patterns indicated several epigenetic subtypes associated with different fusion types. Potential clinical implications are still under evaluation. Age distribution of patients at diagnosis in this cohort ranged from two months to 71 years (median=7.5 years). We observed no gender bias. Survival analyses are currently being performed, first results on survival and follow-up studies will be shown at the symposium. CONCLUSION We show first-of-its-kind data describing a large cohort of CNS sarcomas with CIC or ATXN1 alterations, outlining molecular and clinical characteristics, which may facilitate the development of guidelines for optimal treatment of these tumors based on retrospective response data. New molecular insights may also open up an avenue for targeted therapeutic approaches.

Hit-to-Lead Optimization of the Natural Product Oridonin as Novel NLRP3 Inflammasome Inhibitors with Potent Anti-Inflammation Activity.

Targeting NLRP3 inflammasome with inhibitors is a novel strategy for NLRP3-driven diseases. Herein, hit compound 5 possessing an attractive skeleton was identified from our in-house database of oridonin, and then a potential lead compound 32 was obtained by optimization of 5, displaying two-digit nanomolar inhibition on NLRP3. Moreover, compound 32 showed enhanced safety index (SI) relative to oridonin (IC50 = 77.2 vs 780.4 nM, SI = 40.5 vs 8.5) and functioned through blocking ASC oligomerization and interaction of NLRP3-ASC/NEK7, thereby suppressing NLRP3 inflammasome assembly and activation. Furthermore, diverse agonists-induced activations of NLRP3 could be impeded by compound 32 without altering NLRC4 or AIM2 inflammasome. Crucially, compound 32 possessed tolerable pharmaceutical properties and significant anti-inflammatory activity in MSU-induced gouty arthritis model. Therefore, this work enriched the SAR of NLRP3 inflammasome inhibitors and provided a potential candidate for the treatment of NLRP3-associated diseases.

A Long-Term Retrospective Natural History Study of EFEMP1-Associated Autosomal Dominant Drusen.

To analyze the natural history of EFEMP1-associated autosomal dominant drusen (ADD). In this retrospective observational study of molecularly confirmed patients with ADD, data and retinal imaging were extracted from an in-house database. The main outcome measurements were best-corrected visual acuity (BCVA), refraction, and retinal imaging, including quantitative analyses of the outer nuclear layer (ONL) thickness and pigmented epithelium detachment area, as well as qualitative analyses. The study included 44 patients (34 females and 10 males). The mean ± SD age of symptom onset was 40.1 ± 6.59 years of age (range, 25-52). Fourteen patients were asymptomatic during their entire follow-up. The most common symptoms at presentation were reduced vision (70%) and distortion in central vision (53%). Most subjects were emmetropic. The mean BCVA (logMAR) at baseline was 0.27 ± 0.41 (range, -0.1 to 2.1) in right eyes and was 0.19 ± 0.32 (range, -0.2 to 1.3) in left eyes. After a mean follow-up of 7.9 years, BCVA was reduced to 0.59 ± 0.66 (range, -0.1 to 2.1) in right eyes and 0.5 ± 0.72 (range, -0.1 to 2.4) in left eyes, values that were significantly different than baseline (P<0.0001 and P<0.0014, respectively). Fifteen eyes showed active or inactive choroidal neovascularization (CNV). BCVA differed significantly (P = 0.0004) between eyes with and without CNV at a comparable mean age. The ONL had a slow rate of thinning longitudinally, which significantly correlated with BCVA. Despite the late onset and relatively good prognosis of ADD, CNVs are more frequent than previously reported and are associated with a worse prognosis. Further research is necessary to elucidate gender associations.

Identification and Root Cause Analysis of the Visible Particles Commonly Encountered in the Biopharmaceutical Industry.

Visible particle is an important issue in the biopharmaceutical industry, and it may occur across all the stages in the life cycle of biologics. Upon the occurrence of visible particles, it is often necessary to conduct chemical identification and root cause analysis to safeguard the safety and efficacy of the biotherapeutic products. In this article, we present a number of typical particles and relevant root cause analysis in the categories of extrinsic, intrinsic and inherent particles that are commonly encountered in the biopharma industry. In particular, the optical images of particles obtained both in situ and after isolation are provided, along with the spectral and elemental information. The particle identification was carried out with multiple microscopic and microspectroscopic techniques, including stereo optical microscopy, Fourier transform infrared microscopy, confocal Raman microscopy, scanning electron microscopy and energy dispersive X-ray spectroscopy. Both commercial and in-house spectral databases were used for comparison and identification. In addition to particle identification, our significant efforts are placed on the root cause analysis of the addressed particles with the intention to provide a relatively whole picture of the particle related issues and practical references to particle mitigation for our peers in the biopharmaceutical industry.

Chemical characterization and comparative analysis of different parts of Cocculus orbiculatus through UHPLC-Q-TOF-MS.

Cocculus orbiculatus (L.) DC. (C. orbiculatus) is a medicinal herb valued for its dried roots with anti-inflammatory, analgesic, diuretic, and other therapeutic properties. Despite its traditional applications, chemical investigations into C. orbiculatus remain limited, focusing predominantly on alkaloids and flavonoids. Furthermore, the therapeutic use of C. orbiculatus predominantly focuses on the roots, leaving the stems, a significant portion of the plant, underutilized. This study employed ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) with in-house and online databases for comprehensive identification of components in various plant parts. Subsequently, untargeted metabolomics was employed to analyze differences in components across different harvest periods and plant sections of C. orbiculatus, aiming to screen for distinct components in different parts of the plant. Finally, metabolomic analysis of the roots and stems, which contribute significantly to the plant's weight, was conducted using chemometrics, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), and heatmaps. A total of 113 components, including alkaloids, flavonoids, and organic acids, were annotated across the root, stem, leaf, flower, and fruit, along with numerous previously unreported compounds. Metabolomic analyses revealed substantial differences in components between the root and stem compared to the leaf, flower, and fruit during the same harvest period. PLS-DA and OPLS-DA annotated 10 differentiating components (VIP > 1.5, P < 0.05, FC > 2 or FC < 0.67), with 5 unique to the root and stem, exhibiting lower mass spectrometric responses. This study provided the first characterization of 113 chemical constituents in different parts of C. orbiculatus, laying the groundwork for pharmacological research and advocating for the enhanced utilization of its stem.

High resolution mass spectrometry targeted analysis and suspect screening of pesticide residues in fruit samples and assessment of dietary exposure

Fruits consistently hold a prominent position in healthy dietary habits. Pesticides are used to manage plant diseases, achieve sustainable production, and maintain high food standards. This study utilized a comprehensive analytical technique that involved both targeted analysis and suspect screening. Analysis was conducted using Ultra-high-performance liquid chromatography coupled with hybrid Linear Trap Quadrupole (LTQ)/Orbitrap High Resolution Mass Spectrometry (HRMS) to examine pesticide levels in fruits. The matrices chosen comprised fruit commodities that are commonly consumed in Greece, including table grapes, apples, pears, citrus fruits, and strawberries. The QuEChERS approach was effectively validated for 30 specific pesticides. According to the method acceptance criteria established by SANTE, the QuEChERS method have shown exceptional efficiency in extracting the chosen pesticides, with recovery rates ranging from 70% to 120% in three concentration levels (10, 50, 100 μg kg−1). It also exhibited outstanding linearity, with an R2 more than 0.99. The method exhibited exceptional precision, with relative standard deviations (RSDs) below 20%. Additionally, the combined measurement uncertainty (MU%) was found to be acceptable, remaining below 50%The quantification limits were below 10 μg kg−1 for the majority of the analytes, satisfying the Maximum Residue Levels (MRLs) established by the European Commission. Following targeted analysis, a dietary risk assessment was performed, revealing that both acute and chronic hazard quotients (aHQ and cHQ), along with chronic hazard index (cHI) were below 1, which indicated that the studied commodities are safe for human consumption. In addition, a suspect screening workflow was developed based on an in-house database comprising 355 pesticides commonly applied to the relevant commodities and related transformation products (TPs). Overall, through suspect screening, twenty-two additional pesticides and TPs not included in the target list were identified. Hence, this approach is anticipated to function as proactive alert system guaranteeing the long-term viability of agricultural production.

TREADS: Target Research for Anti-epileptic Drugs Using Data Science

Context: Epilepsy is a common neurological disease and is classified into different types based on features such as the kind of seizure, age of onset, part of brain effected, etc. There are nearly 30 approved anti-epileptic drugs (AEDs) for treating different epilepsies and each drug targets proteins exhibiting a specific molecular mechanism of action. There are many genes, proteins, and microRNAs known to be associated with different epileptic disorders. This rich information on epilepsy-associated data is not available at one single location and is scattered across multiple publicly available repositories. There is a need to have a single platform integrated with the data, as well as tools required for epilepsy research. Methods and Material: Text mining approaches are used to extract data from multiple biological sources. The data is curated and populated within an in-house developed epilepsy database. Machine-learning based models are built in-house to know the probability of a protein being druggable based on the significant protein features. A web interface is provided for the access of the epilepsy database as well as the ML-based tool developed in-house. Results: The epilepsy-associated data is made accessible through a web browser. For a protein of interest, the platform provides all the feature values, and the results generated using different machine learning models are displayed as visualization plots. Conclusions: To meet these objectives, we present TREADS, a platform for epilepsy research community, having both database and an ML-based tool for the study of AED targets. To access TREADS: https://treads-aer.cdacb.in

New records on toxic cyanobacteria from Brazil: Exploring their occurrence and geography

Cyanobacterial Harmful Algal Blooms (CyanoHABs) pose a significant threat to communities globally, impacting ecosystems and public health. This study provides an in-depth review of the current state of cyanotoxins and the distribution of CyanoHABs species in Brazil, while also detailing the methods used for their detection. Four hundred and twenty-one incidents were analyzed from 1993 to 2021, compiling cyanotoxin records and toxic CyanoHABs occurrences. The investigation begins with the first detection of microcystins in 1994 and highlights pivotal moments, like the 1996 “Caruaru Syndrome” outbreak. This event encouraged research and updated cyanotoxin-monitoring guidelines. The Brazilian drought period of 2015–2016 exacerbated cyanobacterial growth and saxitoxin levels, coinciding with Zika-related microcephaly. This study delves into methods used for cyanotoxin analysis, including ELISA, bioassays, HPLC, and LC-MS. Additionally, we investigated the toxicity of 37 cyanobacterial strains isolated from various Brazilian environments. Extracts were tested against Artemia salina and analyzed by LC-MS. Results revealed toxicity in extracts from 49 % of cyanobacterial strains. LC-MS results were analyzed using GNPS MS/MS molecular networking for comparing experimental spectra with those of cyanotoxin standards against in-house databases and the existing literature. Our research underscores the variability in cyanotoxin production among species and over time, extending beyond microcystins. LC-MS results, interpreted through the GNPS platform, revealed six cyanotoxin groups in Brazilian strains. Yet, compounds present in 75 % of the toxic extracts remained unidentified. Further research is crucial for fully comprehending the impact of potentially harmful organisms on water quality and public health management strategies. The study highlights the urgent need for continuously monitoring cyanobacteria and the cyanotoxin inclusion of management in public health policies.

Novel Ralstonia species from human infections: improved matrix-assisted laser desorption/ionization time-of-flight mass spectrometry-based identification and analysis of antimicrobial resistance patterns.

A collection of 161 Ralstonia isolates, including 90 isolates from persons with cystic fibrosis, 27 isolates from other human clinical samples, 8 isolates from the hospital environment, 7 isolates from industrial samples, and 19 environmental isolates, was subjected to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) identification and yielded confident species level identification scores for only 62 (39%) of the isolates, including four that proved misidentified subsequently. Whole-genome sequence analysis of 32 representative isolates for which no confident MALDI-TOF MS species level identification was obtained revealed the presence of seven novel Ralstonia species, including three and four that were isolated from cystic fibrosis or other human clinical samples, respectively, and provided the basis for updating an in-house MALDI-TOF MS database. A reanalysis of all mass spectra with the updated MALDI-TOF MS database increased the percentage of isolates with confident species level identification up to 77%. The antimicrobial susceptibility of 30 isolates mainly representing novel human clinical and environmental Ralstonia species was tested toward 17 antimicrobial agents and demonstrated that the novel Ralstonia species were generally multi-resistant, yet susceptible to trimethoprim/sulfamethoxazole, ciprofloxacin, and tigecycline. An analysis of genomic antimicrobial resistance genes in 32 novel and publicly available genome sequences revealed broadly distributed beta-lactam resistance determinants.IMPORTANCEThe present study demonstrated that a commercial matrix-assisted laser desorption/ionization time-of-flight mass spectrometry identification database can be tailored to improve the identification of Ralstonia species. It also revealed the presence of seven novel Ralstonia species, including three and four that were isolated from cystic fibrosis or other human clinical samples, respectively. An analysis of minimum inhibitory concentration values demonstrated that the novel Ralstonia species were generally multi-resistant but susceptible to trimethoprim/sulfamethoxazole, ciprofloxacin, and tigecycline.

Prevalence of the protective OAS1 rs10774671-G allele against severe COVID-19 in Moroccans: implications for a North African Neanderthal connection

The clinical presentation of COVID-19 shows high variability among individuals, which is partly due to genetic factors. The OAS1/2/3 cluster has been found to be strongly associated with COVID-19 severity. We examined this locus in the Moroccan population for the occurrence of the critical variant rs10774671 and its respective haplotype blocks. The frequency of single-nucleotide polymorphisms (SNPs) in the cluster of OAS immunity genes in 157 unrelated individuals of Moroccan origin was determined using an in-house exome database. OAS1 exon 6 of 71 SARS-CoV-2-positive individuals with asymptomatic/mild disease and 74 with moderate/severe disease was sequenced by the Sanger method. The genotypic, allelic, and haplotype frequencies of three SNPs were compared between these two groups. Finally, males in our COVID-19 series were genotyped for the Berber-specific marker E-M81. The prevalence of the OAS1 rs10774671-G allele in present-day Moroccans was found to be 40.4%, which is similar to that found in Europeans. However, it was found equally in both the Neanderthal GGG haplotype and the African GAC haplotype, with a frequency of 20% each. These two haplotypes, and hence the rs10774671-G allele, were significantly associated with protection against severe COVID-19 (p = 0.034, p = 0.041, and p = 0.008, respectively). Surprisingly, in men with the Berber-specific uniparental markers, the African haplotype was absent, while the prevalence of the Neanderthal haplotype was similar to that in Europeans. The protective rs10774671-G allele of OAS1 was found only in the Neanderthal haplotype in Berbers, the indigenous people of North Africa, suggesting that this region may have served as a stepping-stone for the passage of hominids to other continents.

Clinicopathological role of Cyclin A2 in uterine corpus endometrial carcinoma: Integration of tissue microarrays and ScRNA-Seq.

The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered. UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis. Single-cell RNA-sequencing (scRNA-seq) analysis was performed to explore cell types in UCEC, and the AUCell algorithm was used to investigate the activity of CCNA2 in different cell types. A total of 32 in-house UCEC and 30 normal endometrial tissues as well as 720 UCEC and 165 control samples from public databases were eligible and collected. Integrated calculation showed that the CCNA2 expression was up-regulated in the UCEC tissues (SMD = 2.43, 95% confidence interval 2.23∼2.64). E2F1 and FOXM1 were identified as transcription factors due to the presence of binding peaks on transcription site of CCNA2. CCNA2 predicted worse prognosis in UCEC. However, CCNA2 was not an independent prognostic factor in UCEC. The scRNA-seq analysis disclosed five cell types: B cells, T cells, monocytes, natural killer cells, and epithelial cells in UCEC. The expression of CCNA2 was mainly located in B cells and T cells. Moreover, CCNA2 was active in T cells and B cells using the AUCell algorithm. CCNA2 was up-regulated and mainly located in T cells and B cells in UCEC. Overexpression of CCNA2 predicted unfavorable prognosis of UCEC.

An assessment of professional competencies and skills required for library professionals of management institutions in Kerala (India)

PurposeThis study aims to explore various skills of library professionals working in management institutions of Kerala State, India.Design/methodology/approachA survey method was used by distributing online questionnaire as a data collection tool. The questionnaires were distributed to the library professionals working in management institutions in Kerala State, India.FindingsThe study’s results revealed that the library professionals were competent with managerial, communication and interpersonal skills. Conversely, they were lacking skills in statements such as institutional repository, web 2.0 and social networks. Their familiarity level with reference management tools, research and academic ethics, electronic publishing and management of open-access resources, were also not satisfactory. They need knowledge of other ICT skills such as designing and maintaining in-house databases, video conferencing tools, advanced troubleshooting creating and managing metadata, handling RFID technology and knowledge in solving issues while organizing webinars. Based on the findings, the study has suggested some recommendations which will enable the government/institutions to take appropriate measures to improve their skills.Practical implicationsThis study will enable the policymakers to identify in which area the library professionals are weak and develop a strategy and framework for increasing the level of their skills.Originality/valueThis study provides the views of the library professionals working in management institutions in India and warrants the library professionals to enhance their skills, especially on research ethics and publications and ICT skills.

VirusPredictor: XGBoost-based software to predict virus-related sequences in human data.

Discovering disease causative pathogens, particularly viruses without reference genomes, poses a technical challenge as they are often unidentifiable through sequence alignment. Machine learning prediction of patient high-throughput sequences unmappable to human and pathogen genomes may reveal sequences originating from uncharacterized viruses. Currently, there is a lack of software specifically designed for accurately predicting such viral sequences in human data. We developed a fast XGBoost method and software VirusPredictor leveraging an in-house viral genome database. Our two-step XGBoost models first classify each query sequence into one of three groups: infectious virus, endogenous retrovirus (ERV) or non-ERV human. The prediction accuracies increased as the sequences became longer, i.e. 0.76, 0.93, and 0.98 for 150-350 (Illumina short reads), 850-950 (Sanger sequencing data), and 2000-5000 bp sequences, respectively. Then, sequences predicted to be from infectious viruses are further classified into one of six virus taxonomic subgroups, and the accuracies increased from 0.92 to >0.98 when query sequences increased from 150-350 to >850 bp. The results suggest that Illumina short reads should be de novo assembled into contigs (e.g. ∼1000 bp or longer) before prediction whenever possible. We applied VirusPredictor to multiple real genomic and metagenomic datasets and obtained high accuracies. VirusPredictor, a user-friendly open-source Python software, is useful for predicting the origins of patients' unmappable sequences. This study is the first to classify ERVs in infectious viral sequence prediction. This is also the first study combining virus sub-group predictions. www.dllab.org/software/VirusPredictor.html.

SPDesign: protein sequence designer based on structural sequence profile using ultrafast shape recognition.

Protein sequence design can provide valuable insights into biopharmaceuticals and disease treatments. Currently, most protein sequence design methods based on deep learning focus on network architecture optimization, while ignoring protein-specific physicochemical features. Inspired by the successful application of structure templates and pre-trained models in the protein structure prediction, we explored whether the representation of structural sequence profile can be used for protein sequence design. In this work, we propose SPDesign, a method for protein sequence design based on structural sequence profile using ultrafast shape recognition. Given an input backbone structure, SPDesign utilizes ultrafast shape recognition vectors to accelerate the search for similar protein structures in our in-house PAcluster80 structure database and then extracts the sequence profile through structure alignment. Combined with structural pre-trained knowledge and geometric features, they are further fed into an enhanced graph neural network for sequence prediction. The results show that SPDesign significantly outperforms the state-of-the-art methods, such as ProteinMPNN, Pifold and LM-Design, leading to 21.89%, 15.54% and 11.4% accuracy gains in sequence recovery rate on CATH 4.2 benchmark, respectively. Encouraging results also have been achieved on orphan and de novo (designed) benchmarks with few homologous sequences. Furthermore, analysis conducted by the PDBench tool suggests that SPDesign performs well in subdivided structures. More interestingly, we found that SPDesign can well reconstruct the sequences of some proteins that have similar structures but different sequences. Finally, the structural modeling verification experiment indicates that the sequences designed by SPDesign can fold into the native structures more accurately.