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PubMed2003

Human oral cavity as a model for the study of genome-genome interactions.

The enormous diversity of culturable bacteria within the oral microbial community coupled with experimental accessibility renders the human oral cavity a valuable model to investigate genome-genome interactions. The complex interactions of oral bacteria result in the formation of biofilms on the surfaces of the oral cavity. One mechanism thought to be important in biofilm formation is the coaggregation of bacterial partners. In this paper, we examine the role of coaggregation in oral biofilms and develop protocols to elucidate the spatial organization of bacterial species retained within oral biofilms. To explore these issues, we have employed two experimental systems: the saliva-coated flowcell and the retrievable enamel chip. From flowcell studies, we have determined that coaggregation can greatly influence the ability of an oral bacterial species to grow and be retained within the developing biofilm. To examine the spatial architecture of oral biofilms, fluorescent in situ hybridization protocols were developed that successfully target specific members of the oral microbial community. Together, these approaches provide insight into the development of oral biofilms and expand our understanding of genome-genome interactions.

Bacterial Physiological Phenomena↗

PubMed2005

An improved protocol for the production of AFLP markers in complex genomes by means of capillary electrophoresis.

The amplified fragment-length polymorphism (AFLP) technology is a recently introduced method to investigate genomes of different complexity, from microbial to higher organisms. It is applied to purposes as diverse as identification of species, strain and varieties, investigation of genetic diversity within and between populations, simple and complex trait mapping, and construction of linkage and physical maps. This technology has been designed on the use of primers labelled with radioactivity and on AFLP fragment separation on sequencing gel. We show that the original EcoRI/TaqI AFLP protocol does not perform appropriately when transferred to fluorescent labelling and capillary electrophoresis (CE), and propose an improved protocol for the production of high-quality AFLP markers in fish, rodents and artiodactyles by means of the Beckman-Coulter CEQ2000 automatic DNA sequencer. In addition, we describe the procedure routinely used in our laboratory to obtain binary matrices from AFLP profiles with the aid of Genographer free-share software (vers. 1.6.0, J.J. Benham, Montana State University), able to elaborate original fragment data and convert them to standard graphical formats for phylogenetic analyses. Comparison with radioactive AFLPs in goats confirmed the reliability of the protocol developed for CE. In fact, 107 fragments generated by two primer combinations and identified by both techniques were attributed the same scoring. Compared with traditional methods, the use of capillary systems and automated analysis increases data throughput and scoring reliability, decreasing the overall experimental error.

Animals↗

PubMed2026

Genomic Insights Into the Multimetal Resilience and Biofilm-Templated Nanorod Biosynthesis of Stenotrophomonas bentonitica BII-R7: Bioremediation and Green Nanotechnology Implications.

While microbial metal reduction is widely documented, the genomic determinants that govern the morphological transition from disordered phases to structured nanocrystals remain elusive. Here, we present an integrative study of Stenotrophomonas bentonitica BII-R7, a strain exhibiting exceptional metal resistance and the unique capacity to synthesize crystalline trigonal selenium (t-Se) nanorods. Comparative pangenomic analysis of 38 Stenotrophomonas strains revealed that BII-R7 possesses a notably large accessory genome of 2311 exclusive singletons. We identify a specialized genomic toolkit, absent in all related strains, comprising key metal resistance determinants (e.g., copB, copF, and czcA) alongside extracellular remodelling enzymes (Wzyligase and GH92-glycosyl hydrolase). This unique repertoire confers BII-R7 with significantly higher Cu and Ni tolerance compared to related Stenotrophomonas species, which we hypothesize is fundamental for maintaining metabolic activity in polymetallic environments. RT-qPCR and functional assays confirm that these singletons are not only upregulated under metal stress (e.g., czcA: 42.2-fold) but are also consistent with a critical role in maintaining biofilm resilience. Crucially, we propose a mechanistic model where this unique genetic repertoire governs the assembly of a compositionally distinctive Extracellular Polymeric Substance (EPS). Using a three-state (biofilm, planktonic, EPS-depleted) experiment, we provide direct phenotypic evidence that an intact EPS matrix is required for the efficient transition from amorphous nanospheres to highly ordered crystalline nanorods, and we propose that it acts as a molecular template directing the anisotropic growth of selenium. By bridging genomics and bionanotechnology, this work positions BII-R7 as a promising candidate for sustainable green synthesis and bioremediation, while defining the targeted gene-knockout and complementation experiments now required to establish direct causal roles for the candidate determinants.

Stenotrophomonas↗

PubMed2006

Detection of divergent genes in microbial aCGH experiments.

BACKGROUND: Array-based comparative genome hybridization (aCGH) is a tool for rapid comparison of genomes from different bacterial strains. The purpose of such analysis is to detect highly divergent or absent genes in a sample strain compared to an index strain. Development of methods for analyzing aCGH data has primarily focused on copy number abberations in cancer research. In microbial aCGH analyses, genes are typically ranked by log-ratios, and classification into divergent or present is done by choosing a cutoff log-ratio, either manually or by statistics calculated from the log-ratio distribution. As experimental settings vary considerably, it is not possible to develop a classical discriminant or statistical learning approach. METHODS: We introduce a more efficient method for analyzing microbial aCGH data using a finite mixture model and a data rotation scheme. Using the average posterior probabilities from the model fitted to log-ratios before and after rotation, we get a score for each gene, and demonstrate its advantages for ranking and detecting divergent genes with enlarged specificity and sensitivity. RESULTS: The procedure is tested and compared to other approaches on simulated data sets, as well as on four experimental validation data sets for aCGH analysis on fully sequenced strains of Staphylococcus aureus and Streptococcus pneumoniae. CONCLUSION: When tested on simulated data as well as on four different experimental validation data sets from experiments with only fully sequenced strains, our procedure out-competes the standard procedures of using a simple log-ratio cutoff for classification into present and divergent genes.

Computational Biology↗

PubMed2026

Molecular and Genomic Mechanisms Linking Diabetes Mellitus and Periodontitis: From Pathogenesis to Translational Opportunities.

Diabetes mellitus and periodontitis are bidirectionally associated chronic disorders linked through metabolic dysregulation, host inflammation, microbial dysbiosis, and impaired tissue remodeling. This review summarizes clinical, molecular, cellular, genomic, epigenomic, transcriptomic, and microbial evidence concerning the mechanisms underlying this relationship and their potential translational relevance. Chronic hyperglycemia is associated with advanced glycation end product signaling through the receptor for advanced glycation end products, mitogen-activated protein kinase/nuclear factor-κB activation, reactive oxygen species production, oxidative stress, and NLR family pyrin domain-containing 3 inflammasome activation, which may contribute to enhanced cytokine responses and periodontal tissue injury. Diabetes is also associated with altered neutrophil and macrophage function, increased T helper 17/interleukin-17 signaling, and an elevated receptor activator of nuclear factor-κB ligand/osteoprotegerin ratio, thereby favoring osteoclastogenesis and alveolar bone loss. Conversely, periodontal inflammation and microbial products may contribute to systemic low-grade inflammation, insulin resistance, and metabolic dysregulation. Multi-omics studies have identified shared susceptibility loci, regulatory networks, and disease-associated cell states, although their causal and clinical significance remains incompletely defined. These findings suggest potential roles for integrated medical-dental care, glycemic screening in dental settings, periodontal inflammation control, host-modulatory therapies, and regenerative biomaterials. Further longitudinal and experimental studies are needed to determine their clinical applicability.

Humans↗

PubMed2026

Decoding microbial metabolic complementarity from individual traits to community structuring.

A fundamental challenge in microbiome research lies in elucidating the functional capacity of microbial communities through community membership and genomic data. As community structuring and emergent functional traits are determined by bacterial community metabolic networks, it is important to gain insights into the principles that govern bacteria-bacteria interactions. Here, we applied an integrative framework linking individual strain-level traits to community structuring in a simplified synthetic bacterial community (SSC8) that promotes the growth of ungrafted watermelon. By combining mono- and coculture assays with genome-scale metabolic modeling and metabolomic profiling of spent media, we characterized directional interactions and resource dependencies among community members. Our findings show that positive interactions dominated the community network, accounting for 55% of all pairwise combinations, indicating a high prevalence of growth-promoting effects among strains. Genome-scale metabolic modeling showed that functional divergence among strains enhanced the potential for metabolic complementarity as phylogenetic distance increased. Integrating metabolic modeling with metabolomics further suggested that Pseudomonas azotifigens Q6 not only benefited from all other community members, but also exhibited mutualistic interactions with the other three strains, with metabolite exchange involving compounds such as L-lysine and L-cysteine. Pseudomonas azotifigens Q6 acted as an important driver of community composition by affecting the abundance of several other consortium members in vitro. These findings highlight the role of metabolic complementarity in driving community structuring by promoting selective persistence of specific strains. Our work provides mechanistic insights into microbial interaction networks in vitro and offers a conceptual foundation for the rational design of functionally robust and plant-beneficial microbiomes.

Bacteria↗

PubMed2006

Whole-metagenome amplification of a microbial community associated with scleractinian coral by multiple displacement amplification using phi29 polymerase.

Limitations in obtaining sufficient specimens and difficulties in extracting high quality DNA from environmental samples have impeded understanding of the structure of microbial communities. In this study, multiple displacement amplification (MDA) using phi29 polymerase was applied to overcome these hindrances. Optimization of the reaction conditions for amplification of the bacterial genome and evaluation of the MDA product were performed using cyanobacterium Synechocystis sp. strain PCC6803. An 8-h MDA reaction yielded a sufficient quantity of DNA from an initial amount of 0.4 ng, which is equivalent to approximately 10(5) cells. Uniform amplification of genes randomly selected from the cyanobacterial genome was confirmed by real-time polymerase chain reaction. The metagenome from bacteria associated with scleractinian corals was used for whole-genome amplification using phi29 polymerase to analyse the microbial diversity. Unidentified bacteria with less than 93% identity to the closest 16S rDNA sequences deposited in DNA Data Bank of Japan were predominantly detected from the coral-associated bacterial community before and after the MDA procedures. Sequencing analysis indicated that alpha-Proteobacteria was the dominant group in Pocillopora damicornis. This study demonstrates that MDA techniques are efficient for genome wide investigation to understand the actual microbial diversity in limited bacterial samples.

Animals↗

PubMed2025

Whole genome sequencing analysis of Candida glabrata isolates collected from patients with selected drug-resistant candidiasis hospitalized in Eastern Poland.

The epidemiology data for candidiasis indicate an increase in Candida glabrata infections. Moreover, several reports have shown an increasing number of drug-resistant cases of these infections. The source of drug resistance can often be traced to genetic mutations in genes related to a drug's mechanism of action. Therefore, we conducted whole genome sequencing of several drug-resistant isolates of Candida glabrata collected from patients hospitalized in Eastern Poland to assess whether mutations in selected genes correlated with susceptibility analysis results. The fungal species from patient samples were identified, and the isolated Candida glabrata were subjected to antifungal drug susceptibility testing. The results were interpreted according to the EUCAST and CLSI recommendations. Susceptibility to 5-flucytosine was assessed using the ATB FUNGUS kit. Libraries were prepared according to the NEXTERA XT DNA Library Prep and subsequently sequenced. The outcomes indicated common resistance to two of the three analyzed echinocandins, as well as two cases of simultaneous resistance to echinocandins and selected azole-based drugs. We detected several previously reported mutations in selected resistance-related genes, as well as five that are first described here: ERG5 (M267I), ERG6 (R57K), PDH1 (K438Q, V434I, F600V, V1192S), FCY1 (M129T), and FCY2 (I384F). Neither of the identified nonsynonymous mutations was correlated with the drug resistance demonstrated in the susceptibility testing. Furthermore, we can exclude the possibility of acquired drug resistance, thereby raising questions about the possibility of unknown mechanisms of resistance to azole-based and echinocandin drugs.

Candida glabrata↗

PubMed2006

Comparison of DNA and RNA quantification methods suitable for parameter estimation in metabolic modeling of microorganisms.

Recent developments in cellular and molecular biology require the accurate quantification of DNA and RNA in large numbers of samples at a sensitivity that enables determination on small quantities. In this study, five current methods for nucleic acid quantification were compared: (i) UV absorbance spectroscopy at 260 nm, (ii) colorimetric reaction with orcinol reagent, (iii) colorimetric reaction based on diphenylamine, (iv) fluorescence detection with Hoechst 33258 reagent, and (v) fluorescence detection with thiazole orange reagent. Genomic DNA of three different microbial species (with widely different G+C content) was used, as were two different types of yeast RNA and a mixture of equal quantities of DNA and RNA. We can conclude that for nucleic acid quantification, a standard curve with DNA of the microbial strain under study is the best reference. Fluorescence detection with Hoechst 33258 reagent is a sensitive and precise method for DNA quantification if the G+C content is less than 50%. In addition, this method allows quantification of very low levels of DNA (nanogram scale). Moreover, the samples can be crude cell extracts. Also, UV absorbance at 260 nm and fluorescence detection with thiazole orange reagent are sensitive methods for nucleic acid detection, but only if purified nucleic acids need to be measured.

Colorimetry↗

PubMed2004

Identification of candidate microbial sequences from inflammatory lesion of giant cell arteritis.

Giant cell arteritis (GCA) is a granulomatous inflammatory disease of medium and large arteries which is prevalent in the elderly population. The etiology of GCA is unknown, although the immunologic features suggest the possible presence of a microorganism. Our group has examined whether microbial DNA fragments were present at GCA lesions and whether such microbial fragments could be associated with disease pathogenesis. Initial identification of microbial sequences was performed using genomic representational difference analysis (RDA). Laser dissecting microscopy was used to isolate cells from GCA lesions and adjacent uninvolved temporal artery. Using genomic RDA, we isolated 10 gene fragments; three of these sequences had high homology with prokaryotic genes and were considered high-priority candidates for further study. An examination of serum from GCA(+) individuals (in contrast to healthy age-matched controls) showed the presence of IgG which recognized in vitro translated proteins from these clones.

Amino Acid Sequence↗

PubMed2026

Perseus: Lineage-Aware Refinement of Kraken2 Taxonomic Classification for Long Read Metagenomes.

MOTIVATION: Long-read metagenomic sequencing improves assembly contiguity and enables genome-resolved analysis of complex microbial communities, but accurate taxonomic classification of long reads and assembled contigs remains challenging. Highly scalable k-mer-based classifiers such as Kraken2 frequently over-assign fine-rank taxonomic labels when applied to long-read data, producing high false positive classification rates driven by sparse or localized k-mer matches, particularly in microbiomes with extensive taxonomic novelty. RESULTS: We present Perseus, a lineage-aware confidence estimation framework for taxonomic classification that models the spatial distribution and hierarchical consistency of k-mer evidence along sequences. This formulation reframes taxonomic classification as a hierarchical confidence estimation problem rather than a single-rank prediction task. Perseus refines k-mer-level taxonomic signals from Kraken2 using a multi-headed convolutional neural network that estimates calibrated confidence scores for taxonomic correctness at each canonical rank. Using these estimates, Perseus confirms assignments, backs off to higher taxonomic ranks, or abstains when evidence is insufficient, prioritizing correctness and lineage consistency over overly specific assignments. Across simulations of taxonomic novelty and real-world metagenomic datasets, Perseus consistently and substantially reduces the false assignment rate while improving precision and lineage-consistent accuracy. These improvements are most pronounced for long reads and assembled contigs, where spatial context enables reliable discrimination between consistent taxonomic signal and spurious matches. AVAILABILITY AND IMPLEMENTATION: Perseus integrates with existing Kraken2 workflows and is available at https://github.com/matnguyen/perseus.

Journal Article↗

PubMed2004

MetaCyc: a multiorganism database of metabolic pathways and enzymes.

The MetaCyc database (see URL http://MetaCyc.org) is a collection of metabolic pathways and enzymes from a wide variety of organisms, primarily microorganisms and plants. The goal of MetaCyc is to contain a representative sample of each experimentally elucidated pathway, and thereby to catalog the universe of metabolism. MetaCyc also describes reactions, chemical compounds and genes. Many of the pathways and enzymes in MetaCyc contain extensive information, including comments and literature citations. SRI's Pathway Tools software supports querying, visualization and curation of MetaCyc. With its wide breadth and depth of metabolic information, MetaCyc is a valuable resource for a variety of applications. MetaCyc is the reference database of pathways and enzymes that is used in conjunction with SRI's metabolic pathway prediction program to create Pathway/Genome Databases that can be augmented with curation from the scientific literature and published on the world wide web. MetaCyc also serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. In the past 2 years the data content and the Pathway Tools software used to query, visualize and edit MetaCyc have been expanded significantly. These enhancements are described in this paper.

Biochemical Phenomena↗

PubMed2006

MetaCyc: a multiorganism database of metabolic pathways and enzymes.

MetaCyc is a database of metabolic pathways and enzymes located at http://MetaCyc.org/. Its goal is to serve as a metabolic encyclopedia, containing a collection of non-redundant pathways central to small molecule metabolism, which have been reported in the experimental literature. Most of the pathways in MetaCyc occur in microorganisms and plants, although animal pathways are also represented. MetaCyc contains metabolic pathways, enzymatic reactions, enzymes, chemical compounds, genes and review-level comments. Enzyme information includes substrate specificity, kinetic properties, activators, inhibitors, cofactor requirements and links to sequence and structure databases. Data are curated from the primary literature by curators with expertise in biochemistry and molecular biology. MetaCyc serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. Querying, visualization and curation of the database is supported by SRI's Pathway Tools software. The PathoLogic component of Pathway Tools is used in conjunction with MetaCyc to predict the metabolic network of an organism from its annotated genome. SRI and the European Bioinformatics Institute employed this tool to create pathway/genome databases (PGDBs) for 165 organisms, available at the BioCyc.org website. These PGDBs also include predicted operons and pathway hole fillers.

Animals↗

PubMed2002

Transposable element ISHp608 of Helicobacter pylori: nonrandom geographic distribution, functional organization, and insertion specificity.

A new member of the IS605 transposable element family, designated ISHp608, was found by subtractive hybridization in Helicobacter pylori. Like the three other insertion sequences (ISs) known in this gastric pathogen, it contains two open reading frames (orfA and orfB), each related to putative transposase genes of simpler (one-gene) elements in other prokaryotes; orfB is also related to the Salmonella virulence gene gipA. PCR and hybridization tests showed that ISHp608 is nonrandomly distributed geographically: it was found in 21% of 194 European and African strains, 14% of 175 Bengali strains, 43% of 131 strains from native Peruvians and Alaska natives, but just 1% of 223 East Asian strains. ISHp608 also seemed more abundant in Peruvian gastric cancer strains than gastritis strains (9 of 14 versus 15 of 45, respectively; P = 0.04). Two ISHp608 types differing by approximately 11% in DNA sequence were identified: one was widely distributed geographically, and the other was found only in Peruvian and Alaskan strains. Isolates of a given type differed by < or = 2% in DNA sequence, but several recombinant elements were also found. ISHp608 marked with a resistance gene was found to (i) transpose in Escherichia coli; (ii) generate simple insertions during transposition, not cointegrates; (iii) insert downstream of the motif 5"-TTAC without duplicating target sequences; and (iv) require orfA but not orfB for its transposition. ISHp608 represents a widespread family of novel chimeric mobile DNA elements whose further analysis should provide new insights into transposition mechanisms and into microbial population genetic structure and genome evolution.

Amino Acid Sequence↗

PubMed2025

CoverM: read alignment statistics for metagenomics.

SUMMARY: Genome-centric analysis of metagenomic samples is a powerful method for understanding the function of microbial communities. Calculating read coverage is a central part of analysis, enabling differential coverage binning for recovery of genomes and estimation of microbial community composition. Coverage is determined by processing read alignments to reference sequences of either contigs or genomes. Per-reference coverage is typically calculated in an ad-hoc manner, with each software package providing its own implementation and specific definition of coverage. Here we present a unified software package CoverM which calculates several coverage statistics for contigs and genomes in an ergonomic and flexible manner. It uses "Mosdepth arrays" for computational efficiency and avoids unnecessary I/O overhead by calculating coverage statistics from streamed read alignment results. AVAILABILITY AND IMPLEMENTATION: CoverM is free software available at https://github.com/wwood/coverm. CoverM is implemented in Rust, with Python (https://github.com/apcamargo/pycoverm) and Julia (https://github.com/JuliaBinaryWrappers/CoverM_jll.jl) interfaces.

Metabolomics↗

PubMed1995

How to alter the bacterial genome structure.

Bacterial chromosomes, mostly of circular form, have an unique primary structure that are stably maintained. We initiated a systematic study to induce changes of the structure of the Bacillus subtilis chromosome. There are two main goals: (i) to obtain general concepts for possible plasticity of the bacterial genome and (ii) to apply the proposed genome technology to bacteria.

Bacillus subtilis↗

PubMed2000

Proteomics in medical microbiology.

The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.

Bacterial Proteins↗

PubMed2025

Evolutionary adaptations of a pediatric pathogen: low-inflammatory and high-resistance phenotypes in the emerging Salmonella typhimurium monophasic variant 1,4,[5],12:i:

Salmonella enterica serovar 1,4,[5],12:i:- (S.1,4,[5],12:i:-), a monophasic variant of Salmonella typhimurium (S. typhimurium), is an emerging multidrug-resistant pathogen posing a significant threat to pediatric health. Research on this variant remains limited, and due to challenges associated with traditional identification methods, S.1,4,[5],12:i:- has often been misclassified as S. typhimurium. This study collected clinical data from 122 children infected with S.1,4,[5],12:i:- and 42 with traditional S. typhimurium in Fujian Province, China, between 2014 and 2023. Whole-genome sequencing was used for strain analysis. Our findings revealed that 77.87% of children with S.1,4,[5],12:i:- infection were aged between 1 month and 2 years. Compared with traditional S. typhimurium, children with S.1,4,[5],12:i:- exhibited milder clinical symptoms, as evidenced by lower levels of the inflammatory marker C-reactive protein (16.53 mg/L vs. 33.94 mg/L, P < 0.05) and a lower hospitalization rate (26.23% vs. 42.86%, P < 0.05). These differences may be attributed to the high carriage rate of the anti-inflammatory gene gogB in S.1,4,[5],12:i:- (95.08% vs. 16.67%, P < 0.0001). Additionally, S.1,4,[5],12:i:- exhibited a higher resistance rate to multiple antibiotics, particularly ceftriaxone, than traditional S. typhimurium (32.79% vs. 7.14%, P < 0.001). This increased resistance may be associated with the carriage of the IncHI2/IncHI2A plasmid. The S.1,4,[5],12:i:- ST34 clone prevalent in this region aligns with the global epidemic trend but exhibits greater genetic diversity. Overall, the stealthy evolutionary adaptation of low-inflammation and high-resistance provides novel insights into this variant's global dominance. These findings underscore the importance of heightened clinical awareness and targeted interventions, particularly for vulnerable pediatric populations. IMPORTANCE S.1,4,[5],12:i:- poses a growing global health threat, particularly endangering infants and young children. Characterized by increasing prevalence, multidrug resistance, and diagnostic challenges, this variant demonstrates milder inflammatory responses yet stronger antibiotic resistance than traditional S. typhimurium in pediatric infections. Crucially, we identified its unique "low-inflammation, high-resistance" evolutionary strategy associated with anti-inflammatory gene gogB and resistance plasmid IncHI2/IncHI2A. The stealthy evolutionary adaptation provides novel insights into this variant's global dominance, while offering critical guidance for improving clinical management and formulating targeted public health measures to protect vulnerable pediatric populations against this cunning pathogen.

Humans↗