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Matrix-assisted laser desorption/ionisation, time-of-flight mass spectrometry in genomics research.

The beginning of this millennium has seen dramatic advances in genomic research. Milestones such as the complete sequencing of the human genome and of many other species were achieved and complemented by the systematic discovery of variation at the single nucleotide (SNP) and whole segment (copy number polymorphism) level. Currently most genomics research efforts are concentrated on the production of whole genome functional annotations, as well as on mapping the epigenome by identifying the methylation status of CpGs, mainly in CpG islands, in different tissues. These recent advances have a major impact on the way genetic research is conducted and have accelerated the discovery of genetic factors contributing to disease. Technology was the critical driving force behind genomics projects: both the combination of Sanger sequencing with high-throughput capillary electrophoresis and the rapid advances in microarray technologies were keys to success. MALDI-TOF MS-based genome analysis represents a relative newcomer in this field. Can it establish itself as a long-term contributor to genetics research, or is it only suitable for niche areas and for laboratories with a passion for mass spectrometry? In this review, we will highlight the potential of MALDI-TOF MS-based tools for resequencing and for epigenetics research applications, as well as for classical complex genetic studies, allele quantification, and quantitative gene expression analysis. We will also identify the current limitations of this approach and attempt to place it in the context of other genome analysis technologies.

Animals↗

Combining bioinformatics and phylogenetics to identify large sets of single-copy orthologous genes (COSII) for comparative, evolutionary and systematic studies: a test case in the euasterid plant clade.

We report herein the application of a set of algorithms to identify a large number (2869) of single-copy orthologs (COSII), which are shared by most, if not all, euasterid plant species as well as the model species Arabidopsis. Alignments of the orthologous sequences across multiple species enabled the design of "universal PCR primers," which can be used to amplify the corresponding orthologs from a broad range of taxa, including those lacking any sequence databases. Functional annotation revealed that these conserved, single-copy orthologs encode a higher-than-expected frequency of proteins transported and utilized in organelles and a paucity of proteins associated with cell walls, protein kinases, transcription factors, and signal transduction. The enabling power of this new ortholog resource was demonstrated in phylogenetic studies, as well as in comparative mapping across the plant families tomato (family Solanaceae) and coffee (family Rubiaceae). The combined results of these studies provide compelling evidence that (1) the ancestral species that gave rise to the core euasterid families Solanaceae and Rubiaceae had a basic chromosome number of x=11 or 12.2) No whole-genome duplication event (i.e., polyploidization) occurred immediately prior to or after the radiation of either Solanaceae or Rubiaceae as has been recently suggested.

Algorithms↗

Multidimensional protein identification technology: current status and future prospects.

Protein profiling using high-throughput tandem mass spectrometry has become a powerful method for analyzing changes in global protein expression patterns in cells and tissues as a function of developmental, physiologic and disease processes. This review summarizes the utility and practical application of multidimensional protein identification technology as a platform for comprehensive proteomic profiling of complex biologic samples. The strengths and potential problems and limitations associated with this powerful technology are discussed, with an emphasis placed on one of the biggest challenges currently facing large-scale expression profiling projects -- namely, data analysis. Complementary bioinformatic computational data mining strategies, such as clustering, functional annotation and statistical inference, are also discussed as these are increasingly necessary for interpreting the results of global proteomic profiling studies.

Animals↗

The Schistosoma mansoni gene index: gene discovery and biology by reconstruction and analysis of expressed gene sequences.

Expressed sequence tag (EST) sequencing and analysis is a primary research tool to identify and characterize the Schistosoma mansoni transcriptome. As part of our gene discovery effort, a total of 5,793 ESTs have been generated from clones selected randomly from complementary DNA (cDNA) libraries constructed from male and female adult worms. Assembly analysis of all the 16,813 public S. mansoni ESTs has identified 1,920 distinct tentative consensus sequences (TCs) and 5,571 nonoverlapping ESTs (singletons). Of these, 376 TCs (20%) and 1,449 singletons (26%) are unique to the SUNY/TIGR sequencing effort. Tentative consensus sequences and singletons were distributed into various categories of biological roles associated with cell structure, metabolism, protein fate, signal transduction, transcription, protein synthesis, transporters, and cell growth. The TCs and singletons represent transcripts that can be used as a resource for functional annotation of genomic sequence data, comparative sequence analysis, and cDNA clone selection for microarray projects. The utility of EST analysis is demonstrated by identifying new protease genes, which may be involved in hemoglobin degradation.

Amino Acid Sequence↗

[Effects and mechanisms of ethanol extract of Salvia miltiorrhiza on liver fibrosis in mice].

To identify clinically advantageous TCMs for anti-hepatic fibrosis and to elucidate the effects and molecular mechanisms of Salvia miltiorrhiza ethanol extract in the intervention of liver fibrosis, this study screened high-frequency anti-hepatic fibrosis TCMs through a review of clinical literature. The S. miltiorrhiza active components, potential targets, and liver fibrosis-related disease targets were obtained using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), the GeneCards database, and other databases. Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were performed on the shared targets between drugs and diseases. Molecular docking was conducted to evaluate the binding affinities between key components and core targets. In animal experiments, male Kunming mice were used to establish a liver fibrosis model induced by carbon tetrachloride(CCl_4). The mice were administered low, medium, and high doses of S. miltiorrhiza ethanol extract by gavage. The liver index, as well as serum aspartate aminotransferase(AST) and alanine aminotransferase(ALT) levels, were measured. Histopathological changes in liver tissue were observed using hematoxylin-eosin(HE) staining and Masson's trichrome staining. Western blot analysis was used to detect the protein expression levels of α-smooth muscle actin(α-SMA), Collagen Ⅰ, and heat shock protein 90 alpha family class A member 1(HSP90AA1) in liver tissue. The results showed that S. miltiorrhiza was the most frequently used TCM in clinical anti-hepatic fibrosis. A total of 65 active components and 135 potential targets were identified, and 109 common targets were obtained by intersecting these with liver fibrosis-related targets. The core targets included tumor protein p53(TP53), serine/threonine protein kinase AKT1(AKT1), Jun proto-oncogene(JUN), signal transducer and activator of transcription 3(STAT3), and HSP90AA1, which were mainly enriched in pathways related to cancer, hepatitis B, and the PI3K-AKT signaling pathway. Molecular docking indicated that the main active components of S. miltiorrhiza bound stably to the core targets, with the strongest binding affinity observed for HSP90AA1. Animal experiments demonstrated that the liver index, serum ALT and AST levels, and the expression of α-SMA, Collagen Ⅰ, and HSP90AA1 in liver tissue were significantly increased in the model group, accompanied by obvious pathological manifestations of fibrosis. Compared with the model group, different dose groups of S. miltiorrhiza ethanol extract reduced the liver index and serum ALT and AST levels to varying degrees, alleviated pathological damage and collagen deposition in liver tissue, and downregulated the protein expression of α-SMA, Collagen Ⅰ, and HSP90AA1. In conclusion, S. miltiorrhiza ethanol extract exerts a significant protective effect on CCl_4-induced liver fibrosis in mice, and its mechanisms may be related to the inhibition of HSP90AA1 expression and the regulation of liver fibrosis-related signaling pathways.

Animals↗

Quantitative proteomic analysis of the brain reveals the potential antidepressant mechanism of Jiawei Danzhi Xiaoyao San in a chronic unpredictable mild stress mouse model of depression.

OBJECTIVE: To reveal the antidepressant mechanisms of Jiawei DanZhiXiaoYaoSan (,JD) in chronic unpredictable mild stress (CUMS)-induced depression in mice. METHODS: Using the CUMS mouse model of depression, the antidepressant effects of JD were assessed using the sucrose preference test (SPT), forced swimming test (FST), and tail suspension test (TST). Tandem mass tag (TMT)-based quantitative proteomic analysis of the brain was performed following JD treatment. Hierarchical clustering, Gene Ontology function annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interactions (PPIs) were used to analyze differentially expressed proteins (DEPs), which were further validated using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. RESULTS: Behavioral tests confirmed the anti-depressant effects of JD, and bioinformatics analysis revealed 59 DEPs, including 33 up-regulated and 26 down-regulated proteins, between the CUMS and JD-M groups. KEGG and PPI analyses revealed that neuro-filament proteins and the Ras signaling pathway may be key targets of JD in the treatment of depression. qRT-PCR and Western blotting results demonstrated that CUMS reduced the protein expression of neurofilament light (NEFL) and medium (NEFM) and inhibited the phosphorylation of extracellular regulated kinase 1/2 (ERK1/2), whereas JD promoted the phosphorylation of ERK1/2 and up-regulated the protein expression of NEFL and NEFM. CONCLUSIONS: The antidepressant mechanism of JD may be related to the up-regulation of p-ERK1/2 and neurofilament proteins.

Animals↗

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University M&#xfc;nster.

Journal Article↗

Mammalian RNAi: a practical guide.

Silencing of gene expression by RNA interference (RNAi) has become a powerful tool for the functional annotation of the Caenorhabditis elegans and Drosophila melanogaster genomes. Recent advances in the design and delivery of targeting molecules now permit efficient and highly specific gene silencing in mammalian systems as well. RNAi offers a simple, fast, and cost-effective alternative to existing gene targeting technologies both in cell-based and in vivo settings. Synthetic small interfering RNA (siRNA) and retroviral short hairpin RNA (shRNA) libraries targeting thousands of human and mouse genes are publicly available for high-throughput genetic screens, and knockdown animals can be rapidly generated by lentivirus-mediated transgenesis. RNAi also holds great promise as a novel therapeutic approach. This review provides insight into the current gene silencing techniques in mammalian systems.

Animals↗

Preliminary Exploration on Melatonin-Mediated Protective Effects in Intracranial Aneurysms: Transcriptomic, Proteomic, and Metabolomic Profiling of Cerebral Vascular Tissues Combined with in vivo Animal Experiments.

BACKGROUND: Intracranial aneurysm (IA) is a life-threatening cerebrovascular disease with unclear molecular mechanisms and limited drug treatment. Our previous research has shown that melatonin (MLT) has potential protective effects in IA, but its mechanism remains unclear. The purpose of this study is to explore the pathological mechanism of IA and the therapeutic mechanism of MLT by integrating transcriptomic, proteomic and metabolomic analyses. METHODS: In this study, mouse models of IA were successfully established by combining elastase injection with angiotensin II infusion. C57BL/6 mice were divided into control, IA model, IA model+MLT, and IA model+nimodipine groups. The pathological conditions were evaluated by hematoxylin-eosin (HE) staining, TUNEL staining, and scanning electron microscopy. Transcriptomic (n=3 for each group), proteomic (n=3 for each group), and metabolomic (n=6 for each group) analyses were performed based on cerebral vascular tissue samples. The screening thresholds for differentially expressed genes and differentially expressed proteins were P <0.05 and fold change >1.5 and fold change <0.667. The screening criteria for differential metabolites were variable importance for the projection (VIP)> 1.0, fold change >1.2 and fold change <0.833, and P <0.05. RESULTS: MLT alleviated brain tissue damage, vascular endothelial damage, structural disruption, and apoptosis in IA mice. Transcriptomic, proteomic and metabolomic analyses identified numerous differential molecules. Functional annotation revealed that these molecules may be involved in biological pathways and processes such as immune inflammation, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress and metabolic pathways, thereby regulating the occurrence and development of IA or mediating the therapeutic effects of MLT. Furthermore, transcriptomic and proteomic analyses also suggest that there may be extensive post-transcriptional, translational and post-translational regulatory events in the progression of IA and the therapeutic effects of MLT. Integrated transcriptomic and proteomic analyses suggest that Npy may be a key molecule in regulating IA progression and mediating MLT therapeutic effects, and its potential value is further supported by our immunohistochemical validation results. CONCLUSION: Multi-omics integrative analysis preliminarily revealed that the potential mechanisms of MLT may involve the regulation of inflammatory response, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress, metabolic pathways, and post-transcriptional/translational regulation.

Animals↗

Biomedical literature mining: challenges and solutions in the 'omics' era.

It is now obvious that the rate-limiting step in high throughput experimentation is neither data acquisition nor analysis, but rather our ability to interpret data on a genome-wide scale. Indeed, the explosion of data sampling capacity combined with increasing publication rates greatly impairs our ability to find meaning in vast collections of data. In order to support data interpretation, bioinformatic tools are needed to identify critical information contained in large bodies of literature. However, extracting knowledge embedded in free text is an arduous task, compounded in the biomedical field by an inconsistent gene nomenclature, domain-specific language and restricted access to full text articles. This paper presents a selection of currently available biomedical literature mining software. These tools rely on statistic and, more recently, semantic analyses (Natural Language Processing) to automatically extract information from the literature. In addition, a literature mining strategy has been developed to explore patterns of term occurrences in abstracts. This method automatically identifies relevant keywords in collections of abstracts, and uses a pattern discovery algorithm to generate a visual interface for exploring functional associations among genes. Term occurrence heatmaps can also be combined with gene expression profiles to provide valuable functional annotations. Furthermore, as demonstrated with tumor cell line literature profiling results, this approach can be applied to a variety of themes beyond genomic data analysis. Altogether, these examples illustrate how literature analysis can be employed to support knowledge discovery in biomedical research.

Algorithms↗

Transcriptome Analysis, Machine Learning, and Experimental Identification of CDK7 Affecting the Progression of Pregnancy-induced Hypertension by Influencing Macrophage Polarization.

INTRODUCTION: Pregnancy-induced hypertension (PIH) is a severe pregnancy complication characterized by placental insufficiency, abnormal vascular remodeling, and immune dysregulation, but personalized therapeutic markers remain unclear. This study aimed to identify key genes and explore immune mechanisms in PIH using transcriptome analysis, machine learning, and experimental validation. METHODS: We analyzed the GSE204835 transcriptomic dataset to screen differentially expressed genes (DEGs) and performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Set Enrichment Analysis (GSEA) for functional annotation. Immune infiltration analysis was also performed to examine the immune landscape in PIH. Least Absolute Shrinkage and Selection Operator (LASSO) regression identified key genes, which were validated in a PIH cell model. Flow cytometry and immunofluorescence assays assessed the effect of CDK7 knockdown on macrophage polarization. RESULTS: A total of 1,598 DEGs (1,123 upregulated, 475 downregulated) were identified. Enrichment analyses highlighted associations with embryonic organ development, oxidative phosphorylation, angiogenesis, and oxidative stress. Immune infiltration analysis revealed altered eosinophil and macrophage polarization in PIH. LASSO regression selected 12 key genes, with CDK7 showing the most significant upregulation in the PIH model. CDK7 knockdown promoted macrophage polarization toward the anti-inflammatory M2 phenotype. DISCUSSION: These findings link CDK7 to immune dysregulation in PIH by modulating macrophage polarization, expanding our understanding of PIH's molecular mechanisms. The study's limitations include reliance on public datasets and in vitro models, warranting in vivo validation. CONCLUSION: CDK7 emerges as a potential therapeutic target for PIH, offering new insights into immunoregulatory interventions for this complication.

Female↗

Resources and tools for investigating biomolecular networks in mammals.

Molecular databases serve as primary information resources for the analysis of biological networks providing an essential and invaluable treasure for information exploration. Tools for projecting experimental data sets onto known functional information are a major need to support the analysis of samples produced in clinical research. A new concept is the notation of functional modules, i.e. the characterisation of sets of proteins that perform a defined biological function in cooperation. The determination and analysis of functional modules overcome the limitations of the analysis of individual genes and their properties. Although functional modules are not suitable to fully capture systems properties, they have the potential to unify the information generated by different types of experiments. We describe advances related to the problem of integrating heterogeneous data sets into functional modules for mouse and/or human cellular networks based on publicly available data resources, including advances in the design of ontologies for functional classification, problems of automatic protein functional annotation and integration of microarray data.

Algorithms↗

Gene expression correlates of unexplained fatigue.

Quantitative trait analysis (QTA) can be used to test whether the expression of a particular gene significantly correlates with some ordinal variable. To limit the number of false discoveries in the gene list, a multivariate permutation test can also be performed. The purpose of this study is to identify peripheral blood gene expression correlates of fatigue using quantitative trait analysis on gene expression data from 20,000 genes and fatigue traits measured using the multidimensional fatigue inventory (MFI). A total of 839 genes were statistically associated with fatigue measures. These mapped to biological pathways such as oxidative phosphorylation, gluconeogenesis, lipid metabolism, and several signal transduction pathways. However, more than 50% are not functionally annotated or associated with identified pathways. There is some overlap with genes implicated in other studies using differential gene expression. However, QTA allows detection of alterations that may not reach statistical significance in class comparison analyses, but which could contribute to disease pathophysiology. This study supports the use of phenotypic measures of chronic fatigue syndrome (CFS) and QTA as important for additional studies of this complex illness. Gene expression correlates of other phenotypic measures in the CFS Computational Challenge (C3) data set could be useful. Future studies of CFS should include as many precise measures of disease phenotype as is practical.

Adult↗

Large-scale correlation of DNA accession numbers to the cDNAs in the FANTOM full-length mouse cDNA clone set.

Oligonucleotide-based microarrays, such as GeneChip, are widely used to determine the large-scale gene expression profiles. However, GeneChip only provides information on the identity of the molecules, and the investigator must obtain each cDNA clone for further analyses. In this study, we devised a program which enables us to correlate a large number of DNA accession numbers to the FANTOM (functional annotation of the mouse) full-length mouse cDNA clone set, and made a correlative table between mouse GeneChip clones and FANTOM clones. This allows easy identification of the corresponding FANTOM clone for each GeneChip clone, even if the sequence of the GeneChip clone does not directly match the FANTOM clone. Using this table, for example, a large number of in situ hybridization probes can be synthesized easily, because the FANTOM clones are flanked by T3/T7 promoters on both ends. In addition, we further developed a program which retrieves the amino acid sequence (AA Seq) for each clone, even for the FANTOM clones that lack the AA Seq description, and classifies the proteins automatically. As an example, we devised a correlation table with predictions of the secretory or transmembrane molecules. The correlation table is useful for a large-scale screening of molecules involved in cell-cell communication in various biological processes. The full correlation table for the GeneChip clones is available at http://www.kjm.keio.ac.jp/past/55/3/correlation_table1.html.

Animals↗

Genomic exploration and in silico prioritization of putative COX-2-targeting metabolites from Streptomyces sp. VITGV156 (MCC 4965).

INTRODUCTION: Streptomyces species represent an important source of bioactive natural products, yet systematic genome-guided prioritization of metabolites targeting cyclooxygenase-2 (COX-2/PTGS2) remains limited. This study aimed to investigate the biosynthetic potential of Streptomyces sp. VITGV156 (MCC 4965) using an integrated genome mining and computational drug discovery pipeline. METHODS: Whole-genome sequencing, functional annotation, antiSMASH v7.0.1-based biosynthetic gene cluster (BGC) prediction, LC-MS/MS metabolomic profiling, SwissADME analysis, target prediction, disease association mapping, molecular docking against PTGS2 (PDB: 5IKR), and PASS bioactivity prediction were performed to prioritize putative bioactive metabolites. RESULTS: Genome analysis identified 29 predicted biosynthetic gene clusters, including clusters associated with geosmin, ectoine, albaflavenone, hopene, coelichelin, and SapB, together with several cryptic clusters exhibiting low similarity to known pathways. LC-MS/MS metabolomic profiling provided experimental support for active secondary metabolite production under the cultivation conditions employed. Computational prioritization identified PTGS2 (COX-2) as a biologically relevant target. Molecular docking demonstrated favorable binding affinities and interaction profiles for several predicted metabolites within the PTGS2 catalytic pocket. PASS analysis further suggested potential anticancer-related biological activities that require experimental validation. DISCUSSION: These findings demonstrate the utility of integrating genome mining, metabolomic profiling, and computational drug discovery for prioritizing natural-product candidates. Streptomyces sp. VITGV156 (MCC 4965) represents a promising source of biosynthetic diversity and provides a genome-guided framework for identifying putative COX-2-targeting natural products for future experimental validation rather than confirming metabolite production or biological activity.

COX-2 (PTGS2)↗

Whole-genome sequencing and characterization of Pseudomonas stutzeri P1 endophyte isolated from potato unveils plant growth-promoting and other traits.

Endophytic bacteria play an important role in plant growth promotion and stress tolerance, offering sustainable alternatives to chemical inputs in agriculture. In this study, an endophytic bacterial strain P1 was isolated and identified as Pseudomonas stutzeri, a plant-associated bacterium exhibiting multiple plant growth-promoting traits (PGPTs). Biochemical (qualitative and quantitative) and in vitro analyses demonstrated nitrogen fixation, phosphate solubilization, ammonia production, indole-3-acetic acid (IAA) production, biofilm formation, and tolerance to abiotic stresses, including salinity and drought. Furthermore, the P1 strain displayed strong biocontrol activity against the fungal pathogen Fusarium oxysporum f. sp. cumini, indicating its potential to mitigate biotic stress. Whole-genome sequencing generated a high-quality complete genome of 4,758,235 bp. Functional annotation showed enrichment of metabolic pathways associated with plant-microbe interactions and environmental adaptation. Further analyses using KEGG and PGPT-pred data confirmed the presence of genes associated with direct and indirect PGPT, such as nitrogen fixation, phosphate solubilization, biofilm formation, and stress tolerance. The genome also contained genes related to CAZymes, adhesion, and motility, highlighting a strong plant association, whereas the genome lacked major virulence factors and antimicrobial traits, supporting the non-pathogenic nature of the P1 strain. Overall, these findings demonstrate the potential of P1 as a promising bioinoculant candidate for sustainable agriculture in the potato sector.

PGPT-associated genes↗

Metagenomic profiling of blood-associated microbial DNA signatures in leukemia-associated febrile neutropenia.

Febrile neutropenia (FN) is a life-threatening complication of chemotherapy, but the low microbial biomass of blood makes shotgun metagenomic profiles highly sensitive to technical background. We reanalyzed 47 publicly available patient sequencing runs representing 43 unique patient-timepoint samples from 19 SRA-labeled patients, together with 23 no-template-control (NTC) runs spanning 21 sequencing batches. To distinguish reference-catalogue content from progressively stronger evidence of patient-associated signal, we applied batch-matched NTC correction together with nested abundance thresholds and a feature-specific global NTC envelope. CheckM2 evaluated 1,013 bins; 13 met completeness &#x2265;50% and contamination <10%, and dereplication yielded 11 draft MAG representatives. Ten representatives showed positive patient-to-control abundance excess, but only four showed recurrent support above both threefold matched-control abundance and the global NTC envelope. Functional annotations were therefore interpreted as reference-genome homologs rather than evidence of expression, phenotype, viability or bloodstream origin. Matched-control correction retained 19 read-level ARG types, but only seven subjects contributed complete longitudinal ARG-profile contrasts, limiting reliable temporal inference. The resulting run-resolved, nested evidence framework identified a subset of microbial DNA and ARG signals that remained detectable under increasingly stringent control criteria while distinguishing them from catalogue-level or background-sensitive signals. These findings support cautious reporting of patient-enriched microbial DNA and ARG signals rather than inference of a resident blood microbiome or clinical resistance phenotype.

antimicrobial resistance genes↗

Screening, Physiological Characterization, Genomic Analysis and Optimization by Conjugated Linoleic Acid Bioconversion of Two Lactiplantibacillus plantarum Strains.

Conjugated linoleic acid (CLA) comprises a group of C18 fatty acids containing conjugated double bonds and has been associated with potential anti-obesity and antitumor effects. In this study, 116 presumptive lactic acid bacteria (LAB) isolates were recovered from homemade Sichuan pickles. Primary screening identified 28 CLA-producing isolates, among which strains 7# and 31# showed the highest absorbance at 233 nm (A233). CLA production by both strains was subsequently optimized and quantified using gas chromatography-quadrupole time-of-flight mass spectrometry (GC-Q-TOF). Under the optimized conditions, strain 31# produced 66.50 &#xb1; 3.80 &#x3bc;g/mL total CLA, including 52.70 &#xb1; 3.29 &#x3bc;g/mL c9,t11-CLA and 13.80 &#xb1; 0.51 &#x3bc;g/mL t10,c12-CLA. Strain 7# produced 26.79 &#xb1; 1.09 &#x3bc;g/mL total CLA, including 14.05 &#xb1; 0.49 &#x3bc;g/mL c9,t11-CLA and 12.74 &#xb1; 0.60 &#x3bc;g/mL t10,c12-CLA. Physiological, biochemical, and safety assessments showed that strain 31# outperformed strain 7# overall, supporting its use in further product development and mechanistic studies. Functional annotation using the COG database and pathway mapping with KEGG identified candidate genes encoding an enzyme associated with linoleic acid isomerization in both strains. Potential mechanisms underlying their different CLA-producing capacities were also examined, providing a basis for the selection and development of high-CLA-producing strains.

conjugated linoleic acid↗