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PubMed2026

Characterization and application potential of two newly isolated phages targeting the prevalent multidrug resistant Salmonella serovars in China.

The escalating global threat of multidrug resistant (MDR) Salmonella, a foodborne pathogen with animal-derived foods serving as the primary transmission vehicle, underscores the urgent need for effective lytic phages for biocontrol. From 142 environmental and farm samples in Shandong Province, we isolated 103 phages active against MDR S. Enteritidis and S. Typhimurium, which were the most prevalent Salmonella serovars in China. Two Siphoviridae phages vB-SenS-S1 and vB-SenS-SEC2 were selected for further study. With optimal multiplicities of infection (MOIs) of 10-2 (vB-SenS-S1) and 10-5 (vB-SenS-SEC2), both phages exhibited a 20 min latent period, yielding burst sizes of 52 and 37 PFU/cell, respectively. They also demonstrated stability across a range of temperatures (50-60 °C), pH levels (5-11), and after 1 h of UV exposure. Genomic analysis identified vB-SenS-S1 (43,002 bp, 47.04% GC) and vB-SenS-SEC2 (42,948 bp, 47.65% GC) as novel double-stranded DNA phages. Functional annotation confirmed the presence of genes essential for structural assembly, host lysis, and DNA replication/metabolism, and also verified the absence of resistance, virulence, and lysogeny-associated genes. Both phages vB-SenS-S1 and vB-SenS-SEC2 exhibited synergy with colistin and tetracycline. The synergy with colistin was particularly potent, leading to complete bacterial eradication in vitro. The in vivo therapeutic efficacy was further validated in both Galleria mellonella larvae and murine models of MDR Salmonella infection. Combination therapy with vB-SenS-SEC2 and colistin not only dramatically increased survival but also achieved a significant reduction in bacterial burden across multiple visceral organs of infected mice. Moreover, vB-SenS-S1 (108 PFU/mL) completely inhibited MDR Salmonella on chicken meat at 4 °C and -20 °C when initial contamination was ≤103 CFU/mL. This study not only expands the diversity of Salmonella phages but also highlights their potential as biocontrol agents in both clinical veterinary use and food decontamination, thereby enhancing food quality and safety at both the meat production source and the terminal product.

Animals↗

PubMed2026

Deep learning and statistical methods identify novel asthma risk variants in Europeans.

BACKGROUND: Asthma is a common heritable respiratory disorder with a complex genetic basis. Although large-scale genome-wide association studies have identified many risk loci, the full spectrum of its polygenic architecture remains to be defined. OBJECTIVE: We refined the genetic landscape of asthma in individuals of European ancestry and improve polygenic risk prediction through statistical and deep learning-based methods. METHODS: We conducted the largest genome-wide association study meta-analysis of asthma in individuals of European ancestry, combining data from the Global Biobank Meta-analysis Initiative (121,940 cases, 1,254,131 controls) and the Million Veteran Program (36,823 cases, 398,278 controls). To enhance discovery, we applied pleiotropy-informed multitrait analysis and conditional false discovery rate approaches, each incorporating eosinophil counts as a secondary trait. In parallel, we used a Transformer-based deep learning framework to further prioritize variants and improve polygenic risk prediction. RESULTS: The meta-analysis identified 69 independent genome-wide significant loci (P < 5 × 10-8) not previously reported in asthma. Multitrait analysis of genome-wide association studies, conditional false discovery rate, and deep learning approaches uncovered additional candidate loci. Functional annotation and expression quantitative trait locus mapping implicated novel genes in immune regulation, airway remodeling, and metabolic processes. Polygenic risk score models derived from deep learning-prioritized variants outperformed those based on conventional genome-wide association study and standard statistical approaches. CONCLUSIONS: Our study yields a comprehensive map of asthma-associated loci in European ancestry populations, improves genetic risk prediction, and informs future mechanistic studies.

Humans↗

PubMed2026

The bioinformatics approach to identifying pathogenic variants for colorectal cancer (CRC).

Colorectal cancer (CRC) is the third most prevalent cancer globally, accounting for 9.6% of newly diagnosed cases and 9.3% of cancer-related deaths. It develops from the uncontrolled proliferation of glandular cells in the colon and rectum and is categorized into three primary types: sporadic, hereditary, and colitis-associated. While genetic susceptibility is a key factor in CRC pathogenesis, identifying high-impact pathogenic variants remains a significant challenge. This study integrates bioinformatics and population genetics approaches to identify CRC-associated single-nucleotide polymorphisms (SNPs) with potential clinical significance. CRC-associated SNPs were extracted from the Genome-Wide Association Studies (GWAS) Catalog, functionally annotated via HaploReg, and validated via Ensembl. In addition, expression quantitative trait locus (eQTL) data from the GTEx database were used to assess the effects of these variants on gene expression across human tissues. Our analysis identified three high-priority SNPs (rs9379084, rs3184504, and rs11557154) associated with the RREB1, ATXN2, SH2B3, and DCAF12 genes, which exhibited marked allele frequency differences among populations. These findings suggest potential biomarkers for CRC risk assessment and highlight the importance of genetic screening across diverse populations.

Bioinformatics↗

PubMed2005

In silico discovery of enzyme-substrate specificity-determining residue clusters.

The binding between an enzyme and its substrate is highly specific, despite the fact that many different enzymes show significant sequence and structure similarity. There must be, then, substrate specificity-determining residues that enable different enzymes to recognize their unique substrates. We reason that a coordinated, not independent, action of both conserved and non-conserved residues determine enzymatic activity and specificity. Here, we present a surface patch ranking (SPR) method for in silico discovery of substrate specificity-determining residue clusters by exploring both sequence conservation and correlated mutations. As case studies we apply SPR to several highly homologous enzymatic protein pairs, such as guanylyl versus adenylyl cyclases, lactate versus malate dehydrogenases, and trypsin versus chymotrypsin. Without using experimental data, we predict several single and multi-residue clusters that are consistent with previous mutagenesis experimental results. Most single-residue clusters are directly involved in enzyme-substrate interactions, whereas multi-residue clusters are vital for domain-domain and regulator-enzyme interactions, indicating their complementary role in specificity determination. These results demonstrate that SPR may help the selection of target residues for mutagenesis experiments and, thus, focus rational drug design, protein engineering, and functional annotation to the relevant regions of a protein.

Adenylyl Cyclases↗

PubMed2005

Computational identification and systematic analysis of the ACR gene family in Oryza sativa.

Based on sequence similarity search and domain detection, nine ACT domain repeat protein-coding genes (the "ACR" genes) in rice were identified, which were mainly distributed on the chromosomes 2, 3, 4, and 8. An InterPro database search indicated that four copies of the ACT domain linearly occupied the entire polypeptide. The first three ACT domains were linked by two different sequences. However, the fourth ACT domain was extremely close to ACT3. Gene structure comparisons showed large differences in exon numbers, from three to eight, among members of the rice ACR gene family. In addition, it appeared that gene duplication might be operative when the compositions of exons and introns were analyzed. Phylogenetic analysis divided the ACR gene family into five distinct groups, and this division was generally according to the expression patterns of the ACR genes. The Arabidopsis and rice ACR proteins were clustered across together, suggesting that these ACR genes might originate from an ancient common ancestor. Notably, the identification of orthologues and paralogues would be useful for rice gene functional annotation.

Chromosome Mapping↗

PubMed2026

Genomic and transcriptomic characterization of genes expressed at 20 MPa by the marine actinobacterium Kocuria flava.

A marine hydrocarbonoclastic actinobacterium Kocuria flava IOS11 was isolated from 3500 m deep-sea water of the Indian Ocean. The isolate efficiently degraded phenanthrene (250 mg/L) achieving 82 and 98% of degradation at 0.1 MPa and 20 MPa, respectively within a period of 5 days. Whole genome, transcriptomee and metabolomic analysis elucidated its phenanthrene biodegradation efficiency under in situ deep-sea conditions. The genome sequence comprises 3.47 Mb distributed across 88 scaffolds with a high GC content of 74.30%. The genome analysis encoded 3126 genes including 3052 protein coding sequences with functional annotation identifying a broad array of genes associated with PAHs degradation, environmental stress adaptation, biosurfactant and siderophore synthesis. Transcriptome profiling under 0.1 and 20 MPa conditions with phenanthrene as a sole carbon source revealed enhanced expression of hydrocarbon degrading genes, transporters, biosurfactant associated enzymes and stress responsive genes including integrases, DNA repair protein Rad, alanine ligase, heat and cold shock proteins under high pressure conditions underscoring the deep-sea adaptation capabilities of the strain. The degradation pathway of phenanthrene was proposed through integrated genome, transcriptome and metabolomic analysis. These studies provided K. flava IOS11 as a metabolically versatile and pressure adapted bacterium with promising potential for bioremediation application in extreme marine environment.

Transcriptome↗

PubMed2024

Systematic Proteome Profiling of Maternal Plasma for Development of Preeclampsia Biomarkers.

Preeclampsia (PE) is a hypertensive disorder of pregnancy with various clinical symptoms. However, traditional markers for the disease including high blood pressure and proteinuria are poor indicators of the related adverse outcomes. Here, we performed systematic proteome profiling of plasma samples obtained from pregnant women with PE to identify clinically effective diagnostic biomarkers. Proteome profiling was performed using TMT-based liquid chromatography-mass spectrometry (LC-MS/MS) followed by subsequent verification by multiple reaction monitoring (MRM) analysis on normal and PE maternal plasma samples. Functional annotations of differentially expressed proteins (DEPs) in PE were predicted using bioinformatic tools. The diagnostic accuracies of the biomarkers for PE were estimated according to the area under the receiver-operating characteristics curve (AUC). A total of 1307 proteins were identified, and 870 proteins of them were quantified from plasma samples. Significant differences were evident in 138 DEPs, including 71 upregulated DEPs and 67 downregulated DEPs in the PE group, compared with those in the control group. Upregulated proteins were significantly associated with biological processes including platelet degranulation, proteolysis, lipoprotein metabolism, and cholesterol efflux. Biological processes including blood coagulation and acute-phase response were enriched for down-regulated proteins. Of these, 40 proteins were subsequently validated in an independent cohort of 26 PE patients and 29 healthy controls. APOM, LCN2, and QSOX1 showed high diagnostic accuracies for PE detection (AUC >0.9 and p < 0.001, for all) as validated by MRM and ELISA. Our data demonstrate that three plasma biomarkers, identified by systematic proteomic profiling, present a possibility for the assessment of PE, independent of the clinical characteristics of pregnant women.

Humans↗

PubMed2006

Quorum sensing affects virulence-associated proteins F1, LcrV, KatY and pH6 etc. of Yersinia pestis as revealed by protein microarray-based antibody profiling.

Protein microarray that consists of virulence-associated proteins of Yersinia pestis is used to compare antibody profiles elicited by the wild-type and quorum sensing (QS) mutant strain of this bacterium to define the immunogens that are impacted by QS. The results will lead the way for future functional proteomics studies. The antibody profile that was induced by the QS mutant differed from that of the parent strain. Detailed comparison of the antibody profiles, according to the proteins' functional annotations, showed that QS affects the expression of many virulence-associated proteins of Y. pestis. The antibodies to many virulence-associated proteins were not detected or lower titers of antibodies to many proteins were detected in the sera of rabbits immunized with the QS mutant, relative to those of the wild type, which indicated that these proteins were not expressed or expressed at relatively lower levels in the QS mutant. The results demonstrated that antibody profiling by protein microarrays is a promising high-throughput method for revealing the interactions between pathogens and the host immune system.

Animals↗

PubMed2006

Novel lethal mouse mutants produced in balancer chromosome screens.

Mutagenesis screens are a valuable method to identify genes that are required for normal development. Previous mouse mutagenesis screens for lethal mutations were targeted at specific time points or for developmental processes. Here we present the results of lethal mutant isolation from two mutagenesis screens that use balancer chromosomes. One screen was localized to mouse chromosome 4, between the STS markers D4Mit281 and D4Mit51. The second screen covered the region between Trp53 and Wnt3 on mouse chromosome 11. These screens identified all lethal mutations in the balancer regions, without bias towards any phenotype or stage of death. We have isolated 19 lethal lines on mouse chromosome 4, and 59 lethal lines on chromosome 11, many of which are distinct from previous mutants that map to these regions of the genome. We have characterized the mutant lines to determine the time of death, and performed a pair-wise complementation cross to determine if the mutations are allelic. Our data suggest that the majority of mouse lethal mutations die during mid-gestation, after uterine implantation, with a variety of defects in gastrulation, heart, neural tube, vascular, or placental development. This initial group of mutants provides a functional annotation of mouse chromosomes 4 and 11, and indicates that many novel developmental phenotypes can be quickly isolated in defined genomic intervals through balancer chromosome mutagenesis screens.

Animals↗

PubMed2005

Expression analysis of genes responsible for serotonin signaling in the brain.

To thoroughly understand the function and regulation of neurotransmitter systems in the brain, as well as the underlying disease mechanisms, it is important to comprehensively analyze the expression patterns of genes participating in such systems. Using functional annotated cDNA clones (FANTOM), we examined the gene expression patterns of the serotonin neurotransmitter system, which is involved in psychiatric diseases such as depression. We chose 24 gene products and visualized their endogenous localizations using in situ hybridization (ISH). We were able to fine-tune an automated ISH method to obtain high-resolution cell-based figures within 24 h. We also measured the amounts of mRNAs with quantitative RT-PCR. The outline of the in situ gene expression pattern viewed under low magnification agreed with the results of the RT-PCR. In the high-resolution view obtained with ISH, we could document novel localizations of the several genes critically related to serotonin activity.

Animals↗

PubMed2006

Translational gene mapping of cognitive decline.

The ability to maintain cognitive function during aging is a complex process subject to genetic and environmental influences. Alzheimer's disease (AD) is the most common disorder causing cognitive decline among the elderly. Among those with AD, there is broad variation in the relationship between AD neuropathology and clinical manifestations of dementia. Differences in expression of genes involved in neural processing pathways may contribute to individual differences in maintenance of cognitive function. We performed whole genome expression profiling of RNA obtained from frontal cortex of clinically non-demented and AD subjects to identify genes associated with brain aging and cognitive decline. Genetic mapping information and biological function annotation were incorporated to highlight genes of particular interest. The candidate genes identified in this study were compared with those from two other studies in different tissues to identify common underlying transcriptional profiles. In addition to confirming sweeping transcriptomal differences documented in previous studies of cognitive decline, we present new evidence for up-regulation of actin-related processes and down-regulation of translation, RNA processing and localization, and vesicle-mediated transport in individuals with cognitive decline.

Aged↗

PubMed2005

The Elegance of the MicroRNAs: A Neuronal Perspective.

As knowledge of microRNAs (miRNA) grows from a compendium of sequences to annotated functional data it has become increasingly clear that a highly significant segment of regulatory biology depends on these approximately 22 nucleotide noncoding transcripts. The expression of many miRNAs in the nervous system, some with a high degree of temporal and spatial specificity, suggests that understanding miRNAs in the nervous system will yield rewarding neurobiological insights. High on the list of insights that microRNAs promise is a deeper understanding of the remarkable cellular diversity found among neurons. This review examines the interface between an emerging biology of miRNAs and their role in nervous systems.

Animals↗

PubMed2006

Type III effector proteins: doppelgangers of bacterial virulence.

Bacterial pathogens have co-evolved with their hosts in their ongoing quest for advantage in the resulting interaction. These intimate associations have resulted in remarkable adaptations of prokaryotic virulence proteins and their eukaryotic molecular targets. An important strategy used by microbial pathogens of animals to manipulate host cellular functions is structural mimicry of eukaryotic proteins. Recent evidence demonstrates that plant pathogens also use structural mimicry of host factors as a virulence strategy. Nearly all virulence proteins from phytopathogenic bacteria have eluded functional annotation on the basis of primary amino-acid sequence. Recent efforts to determine their three-dimensional structures are, however, revealing important clues about the mechanisms of bacterial virulence in plants.

Bacteria↗

PubMed2006

Characterization and expression of Arabidopsis UDP-sugar pyrophosphorylase.

At5g52560, a homolog of pea (Pisum sativum) UDP-sugar pyrophosphorylase (PsUSP) was functionally annotated by expression in Escherichia coli and subsequent characterization of substrate specificity and kinetic properties. Arabidopsis contains a single USP gene (AtUSP) and evaluation of gene databases suggests that USP is unique to plants. The 69 kDa AtUSP gene product exhibited high activity with Glc-1-P, GlcA-1-P and Gal-1-P, but low activity with GlcNAc-1-P, Fuc-1-P, Man-1-P, inositol-1-P or Glc-6-P. AtUSP was activated by magnesium and preferred UTP as co-substrate. Apparent K(m) values for GlcA-1-P, Glc-1-P and UTP were 0.13 mM, 0.42 mM and 0.14 mM, respectively. In the reverse direction (pyrophosphorolysis), the apparent K(m) values for UDP-GlcA, UDP-Glc and pyrophosphate were 0.56 mM, 0.72 mM and 0.15 mM, respectively. USP enzyme activity (UDP-GlcA --> GlcA-1-P) was detected in Arabidopsis tissues with highest activity found in the inflorescence. As determined by semi-quantitative RT-PCR, AtUSP transcript is widely expressed with high levels detected in the inflorescence. To evaluate tissue-specific expression of AtUSP, histochemical GUS staining of plants transformed with AtUSPprom:GUS constructs was performed. In 7-day-old seedlings, GUS staining was detected in cotyledons, trichomes and vascular tissues of the primary root. In the inflorescence of older plants, high levels of GUS staining were detected in cauline leaves, the epidermis of the stem and in pollen. In silico analysis of AtUSP expression in developing pollen indicates that transcript levels increase as development proceeds from the uninucleate to the tricellular stage. The results suggest that AtUSP plays an important role in pollen development in Arabidopsis.

Arabidopsis↗

PubMed2005

Predicting protein function from sequence and structural data.

When a protein's function cannot be experimentally determined, it can often be inferred from sequence similarity. Should this process fail, analysis of the protein structure can provide functional clues or confirm tentative functional assignments inferred from the sequence. Many structure-based approaches exist (e.g. fold similarity, three-dimensional templates), but as no single method can be expected to be successful in all cases, a more prudent approach involves combining multiple methods. Several automated servers that integrate evidence from multiple sources have been released this year and particular improvements have been seen with methods utilizing the Gene Ontology functional annotation schema.

Binding Sites↗

PubMed2004

Enhanced functional information from predicted protein networks.

Experimentally derived genome-wide protein interaction networks have been useful in the elucidation of functional information that is not evident from examining individual proteins but determination of these networks is complex and time consuming. To address this problem, several computational methods for predicting protein networks in novel genomes have been developed. A recent publication by Date and Marcotte describes the use of phylogenetic profiling for elucidating novel pathways in proteomes that have not been experimentally characterized. This method, in combination with other computational methods for generating protein-interaction networks, might help identify novel functional pathways and enhance functional annotation of individual proteins.

Energy Metabolism↗

PubMed2005

Pathways to the analysis of microarray data.

The development of microarray technology allows the simultaneous measurement of the expression of many thousands of genes. The information gained offers an unprecedented opportunity to fully characterize biological processes. However, this challenge will only be successful if new tools for the efficient integration and interpretation of large datasets are available. One of these tools, pathway analysis, involves looking for consistent but subtle changes in gene expression by incorporating either pathway or functional annotations. We review several methods of pathway analysis and compare the performance of three, the binomial distribution, z scores, and gene set enrichment analysis, on two microarray datasets. Pathway analysis is a promising tool to identify the mechanisms that underlie diseases, adaptive physiological compensatory responses and new avenues for investigation.

Algorithms↗

PubMed2026

Genome-Wide Association Analyses of Bitter Food Preferences Link Genetic Loci to Sensory and Metabolic Pathways.

BACKGROUND: Genetic variation is implicated in individual preferences for bitter-tasting foods. However, previous studies have focused on candidate genes and limited varieties of bitter-tasting foods and have treated food preference scale responses as continuous data. OBJECTIVES: The present investigation aimed to identify genetic variants associated with preferences for bitter-tasting foods using ordinal multinomial regression models in genome-wide association studies (GWAS). In addition, post-GWAS functional annotation and mapping, genetic correlations, and associations with dietary intake were examined. METHODS: Food preference and genome-wide genotyping data were used from the UK Biobank (n = 125,578). Preference data from Likert scale rankings (from 1 to 9) for 12 individual foods were analyzed using ordinal multinomial regression GWAS. In addition, 1 composite continuous variable was created for preference for cruciferous vegetables as a group and analyzed using a linear mixed-model GWAS to enable the calculation of a polygenic score (PGS) for cruciferous vegetable preference. Convergent validity of GWAS results was assessed with dietary intake data for the same food items in the CARTaGENE cohort (n = 8176). Post-GWAS gene-level and pathway-level association analyses were conducted in MAGMA (Multimarker Analysis of GenoMic Annotation). RESULTS: Forty-six single-nucleotide polymorphisms (SNPs) were identified for preferences for 11 bitter-tasting foods at a genome-wide significance level (P < 7.14 × 10-9). Gene-set analysis for enrichment identified pathways related to caffeine metabolism and bitter taste perception for preference of coffee without sugar and grapefruit, respectively. Genes with higher expression in brain tissues showed stronger genetic associations with cruciferous vegetable preference. The PGS for cruciferous vegetable preference was weakly correlated with intake (r = 0.05, P < 0.0001), but individual SNPs were not associated with intake in a consistent manner. CONCLUSIONS: Genetic variation contributes to preferences for bitter-tasting foods among adults, and some links with food intake are detectable. Nevertheless, effect sizes are small and inconsistent, reflecting the multifactorial complexity of food intake.

bitter taste↗