Nevin Manimala

Environ Microbiome. 2025 Jan 13;20(1):5. doi: 10.1186/s40793-024-00659-1.

ABSTRACT

BACKGROUND: Viruses that infect prokaryotes (phages) constitute the most abundant group of biological agents, playing pivotal roles in microbial systems. They are known to impact microbial community dynamics, microbial ecology, and evolution. Efforts to document the diversity, host range, infection dynamics, and effects of bacteriophage infection on host cell metabolism are extremely underexplored. Phages are classified as virulent or temperate based on their life cycles. Temperate phages adopt the lysogenic mode of infection, where the genome integrates into the host cell genome forming a prophage. Prophages enable viral genome replication without host cell lysis, and often contribute novel and beneficial traits to the host genome. Current phage research predominantly focuses on lytic phages, leaving a significant gap in knowledge regarding prophages, including their biology, diversity, and ecological roles.

RESULTS: Here we develop and describe Prophage-DB, a database of prophages, their proteins, and associated metadata that will serve as a resource for viral genomics and microbial ecology. To create the database, we identified and characterized prophages from genomes in three of the largest publicly available databases. We applied several state-of-the-art tools in our pipeline to annotate these viruses, cluster them, taxonomically classify them, and detect their respective auxiliary metabolic genes. In total, we identify and characterize over 350,000 prophages and 35,000 auxiliary metabolic genes. Our prophage database is highly representative based on statistical results and contains prophages from a diverse set of archaeal and bacterial hosts which show a wide environmental distribution.

CONCLUSION: Given that prophages are particularly overlooked and merit increased attention due to their vital implications for microbiomes and their hosts, we created Prophage-DB to advance our understanding of prophages in microbiomes through a comprehensive characterization of prophages in publicly available genomes. We propose that Prophage-DB will serve as a valuable resource for advancing phage research, offering insights into viral taxonomy, host relationships, auxiliary metabolic genes, and environmental distribution.

PMID:39806487 | DOI:10.1186/s40793-024-00659-1

BMC Res Notes. 2025 Jan 13;18(1):11. doi: 10.1186/s13104-024-07064-4.

ABSTRACT

BACKGROUND: Postharvest lemons are affected by several fungal infections, and as alternatives to chemical fungicides for combating these infections, different microbial biocontrol agents have been studied, with the Clavispora lusitaniae 146 strain standing out. Although strain 146 has proven to be an effective agent, the influence of a microbial biological control agent on the postharvest lemon microbiome has not been studied until now. Thus, this study aimed to evaluate how the epiphytic microbiome of postharvest lemons is affected by the application of the biocontrol yeast C. lusitaniae 146.

RESULTS: In terms of bacterial composition, the most abundant genera were Sphingomonas, Pelomonas, and Bacillus and no significant differences in the composition were detected between the treated and control samples. Among fungi, Clavispora was predominant not only in the treated samples but also in the control, and statistics indicated differences, suggesting its significant role in modulating the epiphytic community composition of lemon. Understanding fruit microbiomes is vital for effective disease control, and this study provides insights into the microbial composition of the surface of lemon and the role of C. lusitaniae 146.

PMID:39806479 | DOI:10.1186/s13104-024-07064-4

Lipids Health Dis. 2025 Jan 13;24(1):12. doi: 10.1186/s12944-024-02426-0.

ABSTRACT

Lipid metabolism in cancer is characterized by dysregulated lipid regulation and utilization, critical for promoting tumor growth, survival, and resistance to therapy. Pancreatic cancer (PC) is a highly aggressive malignancy of the gastrointestinal tract that has a dismal 5-year survival rate of less than 10%. Given the essential function of the pancreas in digestion, cancer progression severely disrupts its function. Standard treatments for PC such as surgical resection, chemotherapy, and radiotherapy. However, these therapies often face significant challenges, including biochemical recurrence and drug resistance.Given these limitations, new therapeutic approaches are being developed to target tumor metabolism. Dysregulation of cholesterol biosynthesis and alterations in fatty acids (FAs), such as palmitate, stearate, omega-3, and omega-6, have been observed in pancreatic cancer. These lipids serve as energy sources, signaling molecules, and essential components of cell membranes. Their accumulation fosters an immunosuppressive tumor microenvironment that supports cancer cell proliferation and metastasis.Moreover, lipid metabolism dysregulation within immune cells, particularly T cells, impairs immune surveillance and weakens the body’s defenses against cancer. Abnormal lipid metabolism also contributes to drug resistance in PC. Despite these challenges, targeting lipid metabolism may offer a promising therapeutic strategy. By enhancing lipid peroxidation, the induction of ferroptosis-a form of regulated cell death-could impair the survival of PC cells and hinder disease progression.

PMID:39806478 | DOI:10.1186/s12944-024-02426-0

J Health Popul Nutr. 2025 Jan 13;44(1):8. doi: 10.1186/s41043-025-00739-z.

ABSTRACT

BACKGROUND: Socioeconomic inequality in nutritional status as one of the main social determinants of health can lead to inequality in health outcomes. In the present study, the socioeconomic inequality in the burden of nutritional deficiencies among the countries of the world using Global Burden of Disease (GBD) data was investigated.

METHODS: Burden data of nutritional deficiencies and its subsets including protein-energy malnutrition, iodine deficiency, vitamin A deficiency, and dietary iron deficiency form GBD study and Human Development Index (HDI), a proxy for the socio-economic status of countries, from united nations database were collected. After descriptive statistics, the concentration index (CI) curve was used to measure socioeconomic inequality. CI for nutritional deficiencies was estimated based on Disability Adjusted Life Years (DALY), Years Lived with Disability (YLD), Years of Life Lost (YLL), prevalence, incidence and death indices. Moreover, CI of DALY and prevalence was estimated and reported for four nutritional deficiencies subgroups.

RESULTS: CIs for DALY, YLD, YLL, prevalence, incidence and death rate show negative values and their, which indicates the concentration of nutritional deficiencies burden among lower HDI countries. The highest value of CI (lowest inequality) for DALY was related to iodine deficiency (-0.3401) and the lowest (highest inequality) was related to vitamin A deficiency (-0.5884). Also, the highest value of CI for prevalence was related to protein-energy malnutrition (-0.1403) and the lowest was related to vitamin A deficiency (-0.4308). Results also show the inequality in DALY was greater than the disparity in prevalence for all subgroups of nutritional deficiencies.

CONCLUSIONS: Inequality in burden of nutritional deficiencies and protein-energy malnutrition, iodine deficiency, vitamin A deficiency and dietary iron deficiency are concentrated in countries with low HDI, so there is pro- poor inequality. Findings indicate that although malnutrition occurs more in low-income countries, due to the weakness of health care systems in these countries, the inequality in the final consequences of malnutrition such as DALY becomes much deeper. More attention should be paid to the development of prevention and primary treatment measures in low HDI countries, such as improving nutrition-related health education, nutritional support and early aggressive treatment, and also eliminating hunger.

PMID:39806471 | DOI:10.1186/s41043-025-00739-z

BMC Med Inform Decis Mak. 2025 Jan 13;25(1):18. doi: 10.1186/s12911-024-02848-x.

ABSTRACT

BACKGROUND: This systematic review aims to explore the early predictive value of machine learning (ML) models for the progression of gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM).

METHODS: A comprehensive and systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science up to July 02, 2024. The quality of the studies included was assessed. The risk of bias was assessed through the prediction model risk of bias assessment tool and a graph was drawn accordingly. The meta-analysis was performed using Stata15.0.

RESULTS: A total of 13 studies were included in the present review, involving 11,320 GDM patients and 22 ML models. The meta-analysis for ML models showed a pooled C-statistic of 0.82 (95% CI: 0.79 ~ 0.86), a pooled sensitivity of 0.76 (0.72 ~ 0.80), and a pooled specificity of 0.57 (0.50 ~ 0.65).

CONCLUSION: ML has favorable diagnostic accuracy for the progression of GDM to T2DM. This provides evidence for the development of predictive tools with broader applicability.

PMID:39806461 | DOI:10.1186/s12911-024-02848-x

BMC Pharmacol Toxicol. 2025 Jan 13;26(1):6. doi: 10.1186/s40360-024-00831-w.

ABSTRACT

Hepatic encephalopathy (HE) is a syndrome that arises from acute or chronic liver failure. This study was devised to assess the impact of a combination of boswellic acid (BA) and low doses of gamma radiation (LDR) on thioacetamide (TAA)-induced HE in an animal model. The effect of daily BA treatment (175 mg/kg body weight, for four weeks) and/or fractionated low-dose γ-radiation (LDR; 0.25 Gy, twice the total dose of 0.5 Gy) was evaluated against TAA (200 mg/kg, intraperitoneal) twice-weekly for four weeks to induce liver damage and HE in rats. TAA-exposed rats exhibited a significant elevation in serum activities of liver enzymes (GGT, ALP) and plasma ammonia levels at P < 0.05 (Duncan’s test) compared to the control group. Moreover, there was an increase in the levels of proinflammatory cytokines (IL6, IL12, IL18) in the TAA-exposed animals accompanied by a depletion in the activities of paraoxonase-1 and neurotransmitter contents compared with normal control rats (P < 0.05). However, the administration of BA alone or in combination with LDR led to improvements in liver and brain parameter indices. Furthermore, the histopathological assessments of liver and brain tissues supported the findings of the biochemical investigations. From the statistical analysis, it can be concluded that the combined administration of BA and exposure to LDR may possess potential hepatoprotective effects against hepatic encephalopathy-associated hyperammonemia and the consequent damage to the liver and brain. This study proposes that a combination of therapeutic approaches, LDR and BA could be a new therapeutic candidate for the management of hepatic encephalopathy.

PMID:39806460 | DOI:10.1186/s40360-024-00831-w

Health Res Policy Syst. 2025 Jan 13;23(1):8. doi: 10.1186/s12961-024-01271-y.

ABSTRACT

During public health crises such as pandemics, governments must rapidly adopt and implement wide-reaching policies and programs (“public policy interventions”). A key takeaway from the coronavirus disease 2019 (COVID-19) pandemic was that although numerous randomized controlled trials (RCTs) focussed on drugs and vaccines, few policy experiments were conducted to evaluate effects of public policy interventions across various sectors on viral transmission and other consequences. Moreover, many quasi-experimental studies were of spurious quality, thus proving unhelpful for informing public policy. The pandemic highlighted the need to continuously develop competence, capacity and a robust legal-ethical foundation for impact evaluations well before crises occur. It raised a crucial question: how can governments in non-crisis times develop capabilities to generate evidence on the effects of public policy interventions, thus enabling a rapid and effective research response during public health crises? We conducted a mapping to explore how government agencies in Norway use RCTs and quasi-experimental methods to strengthen the evidence base for public policy interventions and to identify barriers and facilitators to their use. Contributing to the study were 10 government agencies across sectors such as development assistance, education, health, social welfare, statistics and taxation. Many of these agencies have conducted or commissioned RCTs or quasi-experimental studies in the past 5 years, with evaluations ranging from 1 or 2 to more than 15 per agency. The measures evaluated included organizational, educational and financial interventions and interventions for oversight and sanctions. Some agencies have internal capabilities for designing and conducting evaluations, while others commissioned such studies to universities and other research institutions. Agencies reported examples where enhanced communication among implementers, researchers, ministries and political leaders facilitated impact evaluations, and these lessons offer opportunities for cross-sector knowledge-sharing to help strengthen rigorous evaluations of public policy interventions. Despite their potential, various government agencies report that randomized and quasi-experimental studies face legal, ethical, political and practical barriers that affect their use. For instance, the urgency of politicians to implement policies at scale has led to the discontinuation of trials and hindered learning from their effects. The surveyed agencies stressed the importance of legislation providing clear guidelines on when differential treatment can be justified and when informed consent requirements can be waived, as well as faster and clearer processes for managing privacy concerns related to data access. Crucially, greater political acceptance for systematically and gradually implementing reforms, including using randomization, could strengthen evidence-informed public policy, enhancing the scaling-up of effective interventions and deprioritizing ineffective ones.

PMID:39806454 | DOI:10.1186/s12961-024-01271-y

J Cheminform. 2025 Jan 13;17(1):4. doi: 10.1186/s13321-025-00946-0.

ABSTRACT

Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode. Fragmenstein either takes the atomic coordinates of ligands from a experimental fragment screen and combines the atoms together to produce a novel merged virtual compound, or uses them to predict the bound complex for a provided molecule. The molecule is then energy minimised under strong constraints to obtain a structurally plausible conformer. The code is available at https://github.com/oxpig/Fragmenstein .Scientific contributionThis work shows the importance of using the coordinates of known binders when predicting the conformation of derivative molecules through a retrospective analysis of the COVID Moonshot data. This method has had a prior real-world application in hit-to-lead screening, yielding a sub-micromolar merger from parent hits in a single round. It is therefore likely to further benefit future drug design campaigns and be integrated in future pipelines.

PMID:39806443 | DOI:10.1186/s13321-025-00946-0

Respir Res. 2025 Jan 13;26(1):16. doi: 10.1186/s12931-024-03086-5.

ABSTRACT

BACKGROUND: The emergence of new molecular targeted drugs marks a breakthrough in asthma treatment, particularly for severe cases. Yet, options for moderate-to-severe asthma treatment remain limited, highlighting the urgent need for novel therapeutic drug targets. In this study, we aimed to identify new treatment targets for asthma using the Mendelian randomization method and large-scale genome-wide association data (GWAS).

METHODS: We utilized GWAS data from the UK Biobank (comprising 56,167 patients and 352,255 control subjects) and the FinnGen cohort (including 23,834 patients and 228,085 control subjects). Genetic instruments for 734 plasma proteins and 154 cerebrospinal fluid proteins were derived from recently published GWAS. Bidirectional Mendelian randomization analysis, Steiger filtering, colocalization, and phenotype scanning were employed for reverse causal inference detection, further substantiating the Mendelian randomization results. A protein-protein interaction network was also constructed to reveal potential associations between proteins and asthma medications.

RESULTS: Under Bonferroni significance conditions, Mendelian randomization analysis revealed causal relationships between seven proteins and asthma. In plasma, we observed that an increase of one standard deviation in IL1R1[1.30 (95% CI 1.20-1.42)], IL7R[1.07 (95% CI 1.04-1.11)], ECM1[1.03 (95% CI 1.02-1.05)], and CD200R1[1.18 (95% CI 1.09-1.27)] were associated with an increased risk of asthma, while an increase in ADAM19 [0.87 (95% CI 0.82-0.92)] was found to be protective. In the brain, each 10-fold increase in IL-6 sRa [1.29 (95% CI 1.15-1.45)] was associated with an increased risk of asthma, while an increase in Layilin [0.61 (95% CI 0.51-0.73)] was found to be protective. None of the seven proteins exhibited a reverse causal relationship. Colocalization analysis indicated that ECM1 (coloc.abf-PPH4 = 0.953), IL-6 sRa (coloc.abf-PPH4 = 0.966), and layilin (coloc.abf-PPH4 = 0.975) shared the same genetic variation as in asthma.

CONCLUSION: A causal relationship exists between genetically determined protein levels of IL1R1, IL7R, ECM1, CD200R1, ADAM19, IL-6 sRa, and Layilin (LAYN) and asthma. Moreover, the identified proteins may serve as attractive drug targets for asthma, especially ECM1 and Layilin (LAYN). However, further research is required to comprehensively understand the roles of these proteins in the occurrence and progression of asthma.

PMID:39806440 | DOI:10.1186/s12931-024-03086-5

Orphanet J Rare Dis. 2025 Jan 13;20(1):21. doi: 10.1186/s13023-024-03484-4.

ABSTRACT

BACKGROUND: Intestinal Behçet’s syndrome (IBS) has high morbidity and mortality rates with serious complications. However, there are few specific biomarkers for IBS. The purposes of this study were to investigate the distinctive metabolic changes in plasma samples between IBS patients and healthy people, active IBS and inactive IBS patients, and to identify candidate metabolic biomarkers which would be useful for diagnosing and predicting IBS.

METHODS: In this study, we performed a global untargeted metabolomics approach in plasma samples from 30 IBS patients and 20 healthy subjects. P value < 0.05 and variable importance projection (VIP) values > 1 were considered to be statistically significant metabolites. Univariate receiver operating characteristic (ROC) curve analysis was plotted as a measure for assessing the clinical performance of metabolites, and area under curve (AUC) were assessed.

RESULTS: A total of 147 differentially abundant metabolites (DAMs) were identified between IBS patients and normal control (NC) group. The potential pathways involved in the pathogenesis of IBS include linoleic acid metabolism; GABAergic synapse; biosynthesis of unsaturated fatty acids; valine, leucine and isoleucine biosynthesis; ovarian steroidogenesis; and others. In addition, a total of 103 significant metabolites were selected to distinguish active IBS from inactive IBS patients. Tyrosine metabolism, dopaminergic synapse and neuroactive ligand-receptor interaction were found to be closely related to the disease activity of IBS. Furthermore, three potential metabolites including quinate, stearidonic acid (SDA) and capric acid (CA) could significantly differ IBS patients from NC group. On the other hand, 1-methyladenosine (m1A), genipin, methylmalonic acid (MMA) and ascorbate could significantly differentiated active IBS from inactive IBS patients.

CONCLUSION: In conclusion, this study demonstrated the characteristic plasma metabolic profiles between IBS group and NC group, as well as between active and inactive IBS patients by using an untargeted LC/MS metabolomics profiling approach. In this study, quinate, SDA and CA were identified as potential diagnostic biomarkers for IBS. Additionally, m1A, genipin, MMA and ascorbate could serve as potential biomarkers for evaluating IBS activity. These findings might provide potential valuable insights for developing therapeutic strategies to manage IBS in the future.

PMID:39806438 | DOI:10.1186/s13023-024-03484-4