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PubMed2026

Comparative genomic analysis of Streptococcus parasuis and Streptococcus suis reveals mobile element-associated enrichment of antimicrobial resistance and lack of detectable same-MGE colocalization with virulence-associated genes within stable species boundaries.

Streptococcus suis is a major porcine pathogen and a zoonotic agent that causes meningitis and septicemia in humans. Streptococcus parasuis, a recently recognized close relative, remains poorly characterized with regard to its clinical significance and genomic features. In this study, we generated a single-contig closed genome assembly with genome-wide DNA methylation profiles for S. parasuis strain A1, isolated from a diseased pig in Xinjiang, China, and complemented in silico genomic predictions with isolate-level experimental validation of antimicrobial resistance (AMR) genotypes, virulence genotypes, and phenotypic susceptibility for this reference strain. Using this high-quality genome as a reference anchor, we performed comparative genomic analyses across 195 streptococcal genomes, comprising 15 S. parasuis and 180 S. suis strains, to distinguish genome-level co-occurrence of resistance and virulence determinants from their physical colocalization on the same mobile genetic element (MGE).Species boundaries remained clearly delineated at the genomic level, with a median interspecies average nucleotide identity (ANI) of approximately 86.0%, compared with intraspecies ANI medians of 97.5% for S. parasuis and 96.2% for S. suis. Pangenome analysis identified 12,693 gene clusters, of which 1086 were core clusters, and functional annotation revealed significant differences in accessory gene repertoires between the two species. Within this stable genomic framework, S. parasuis genomes carried a higher AMR gene burden; strain A1 harbored 10 AMR genes, multiple virulence-associated genes, three genomic islands, and eight prophage regions. For strain A1, PCR validation confirmed six AMR genes and six virulence genes, and disk diffusion testing demonstrated a multidrug-resistant phenotype consistent with the genotypic profile.Among 235 predicted mobile elements, 19 harbored AMR genes and seven carried Virulence Factor Database (VFDB) homologs, but none carried both categories simultaneously. This finding reflects a lack of detectable same-MGE colocalization under the applied annotation and assembly framework; it should not be interpreted as evidence of biological physical decoupling. Under a random-placement model, the expected number of co-carrying regions was only 0.57, and the probability of observing zero co-carrying regions was P = 0.55. This negative result should be interpreted with caution, given the limited number of cargo-bearing regions and the predominantly draft status of most genomes. Furthermore, the A1 genome contained multiple restriction-modification systems, showed depletion of several methylation motif families in mobile regions, and had limited CRISPR spacer matching evidence, suggesting prior exposure to the relevant sequence space. None of the genomes met our predefined criteria for whole-genome convergence.Collectively, our results support a model in which S. parasuis accumulates AMR-related genes in a modular fashion via mobile elements within stable species boundaries, with no detectable same-MGE colocalization of AMR and virulence determinants under our analytical pipeline. These findings imply that AMR surveillance strategies for this species should prioritize tracking mobile genetic elements rather than inferring wholesale genomic convergence toward S. suis.

Streptococcus suis↗

PubMed1998

A highly efficient method for the site-specific integration of transfected plasmids into the genome of mammalian cells using purified retroviral integrase.

Using purified bovine leukemia virus (BLV) integrase with liposome, we developed a highly efficient method for the site-specific integration of plasmid vectors into the genome of cultured mammalian cells. The presence of the BLV integrase recognition sequence (IRS) in both the host genome and the plasmid vector to be transfected was required for this integration. The integration occurred within the IRS pre-introduced into the host genome and resulted in a complete or partial deletion of the sequence and an adjacent drug-resistant gene. This site-specific integration was not observed upon transfection without the integrase or with vectors harboring no IRS. This novel method may be useful for manipulating a mammalian genome or for targeting a retroviral genome integrated into a virus-infected cell by using the virus-specific integrase and LTR sequence.

Binding Sites↗

PubMed2026

Integrating multi-omics technologies to decipher microbiome functions.

Multi-omics approaches have revolutionized our understanding of microbial communities by enabling simultaneous interrogation of genomic, transcriptomic, proteomic, and metabolomic data. The systematic integration and analysis of these deep datasets help decipher the functional roles of microbiomes, providing critical insights into microbial activities, interactions, and dynamics across diverse environments. Biological complexity makes multi-omics analysis of a single, isolated organism demanding but highly informative, yet this complexity increases further when samples comprise hundreds to thousands of individual species. As microbiome research continues to expand into clinical, environmental, and engineered systems, standardized workflows, benchmarked datasets, and community-driven initiatives are essential to ensure reproducibility, standardization and interpretability. Establishing and disseminating best practices for experimental design, data processing, and integrative analyses will be critical for maximizing comparability and scientific rigor across studies. This perspective highlights recent advances in multi-omics microbiome research, outlines key obstacles in data integration and metadata harmonization, and proposes a collaborative roadmap for scalable, FAIR-compliant multi-omics investigations and potentially disruptive Artificial Intelligence (AI) advances comparable to those of AlphaFold in the field of microbiome science.

Multiomics↗

PubMed2026

Molecular determinants associated with resistance to imipenem and imipenem-relebactam in clinical Pseudomonas aeruginosa isolates.

BACKGROUND: Pseudomonas aeruginosa accounts for 10-20% of hospital-acquired infections and is a major pathogen in immunocompromised patients. Combination therapies with beta-lactam antibiotics and beta-lactamase inhibitors, such as imipenem-relebactam have improved treatment options, yet resistant strains have already emerged, with mechanisms still not fully elucidated. RESULTS: We sequenced and analyzed 10 clinical P. aeruginosa isolates resistant to imipenem-relebactam (IMI/REL) and compared them with publicly available genomes of imipenem-resistant (IMI-R) and imipenem-susceptible (IMI-S) strains. Resistance genes were identified using the RGI CARD database, while amino acid variations in core-genome proteins were evaluated through Gene Ontology overrepresentation analysis (GO), followed by GWAS. In total, 15,758 ARGs were detected, 25.85% associated with carbapenem resistance, but only 568 classified as beta-lactamases. Among IMI/REL isolates, 36.36% carried Ambler class A and 54.54% class B beta-lactamases, contrasting with much lower frequencies in IMI-R (5.4% and 3.6%) and IMI-S (0% and 0.73%). Core-genome analysis revealed 1,106 proteins with resistance-associated variations. Comparative analyzes identified 1,618 proteins differing between IMI/REL and IMI-R genomes, and 1,015 differing between IMI/REL and all other strains. GWAS highlighted candidate genes with strong statistical associations, including those involved in metal ion transport (e.g., tonB, foxA, phuR, pfeA) and efflux pumps (e.g., czcB), as well as regulators such as mexT and biofilm-related proteins. CONCLUSIONS: These findings suggest that, beyond classical beta-lactamases, resistance may be associated with multifactorial contributions from periplasmic and outer membrane proteins, metal ion homeostasis, efflux regulation, and biofilm-associated pathways. Our results expand current knowledge of P. aeruginosa resistome and highlight novel genomic signatures potentially driving resistance to imipenem-relebactam.

Imipenem↗

PubMed2026

Investigating mechanisms of divergent feed efficiency in dairy cows.

Objectives were to investigate the associations between residual DMI (RFI), calculated as the difference between observed minus predicted DMI, with rumen microbiome, digestion, behavior, and metabolism that might explain the differences in RFI in lactating cows. One hundred 50 genotyped Holstein cows in 3 cohorts were used in this cohort study in which exposure was RFI. Rumen microbiota from 114 cows were sequenced, and a subset of 30 cows was used for hepatic mitochondrial respiration analysis. Cows were ranked by RFI and grouped into quartiles (Q1, most efficient, to Q4, least efficient) according to phenotypic (pQ) or genomic (gQ) quartiles of RFI for data presentation. Statistical models fitted the linear and quadratic RFI as continuous explanatory variables. Increasing efficiency, i.e., from larger to smaller RFI values, whether phenotypic or genomic, were associated with reduced DMI, a 3.0 kg/d difference between Q4 and Q1 according to phenotypic RFI (pRFI) and 1.9 kg/d according to genomic RFI (gRFI) without compromising ECM or body tissue reserves. These differences between Q4 and Q1 of pRFI and gRFI resulted in increased feed conversion ratio by an additional 200 and 100 g of ECM/kg DMI, respectively. Both pRFI and gRFI were associated with FA profiles in milk fat, with decreasing proportions of de novo and mixed FA and increasing proportions of pre-formed FA, particularly monounsaturated FA, as efficiency improved. Additionally, pRFI and gRFI were moderately correlated (r = 0.48) and ranking of cows was consistent across the 2 grouping methods (ρ = 0.44). Reducing RFI was associated with less total rumination time, but greater rumination time per kg of DMI by 2.0 and 1.7 min/kg between the extreme quartiles of pRFI and gRFI, respectively. Phenotypically and genomically more efficient cows were associated with less microbial α diversity based on inverse Simpson index. A total of 57 amplicon sequence variant groups were differentially abundant between Q1 and Q4 classified based on pRFI and gRFI, with Prevotella and Succinivibrionaceae shared between phenotypic and genomic RFI classifications. Increasing phenotypic and genomic efficiency was associated with an increased concentration of ruminal NH3-N. Genomically more efficient cows tended to have reduced ruminal pH (gQ1 to gQ4; 6.42 vs. 6.47 vs. 6.43 vs. 6.53) despite eating less. Decreasing pRFI was associated with reduced microbial N yield whereas, it tended to increase microbial N yield relative to the amount of N intake. Collectively, phenotypic and genomic RFI have a moderate degree of agreement matching the estimated heritability of the trait, and mechanisms underlying improved feed efficiency were linked with differences in ruminal microbiota and fermentation, and with increased rumination per kg of DM rather than total-tract digestibility or hepatic mitochondrial respiration.

dairy cow↗

PubMed2004

Encoding microbial metabolic logic: predicting biodegradation.

Prediction of microbial metabolism is important for annotating genome sequences and for understanding the fate of chemicals in the environment. A metabolic pathway prediction system (PPS) has been developed that is freely available on the world wide web (http://umbbd.ahc.umn.edu/predict/), recognizes the organic functional groups found in a compound, and predicts transformations based on metabolic rules. These rules are designed largely by examining reactions catalogued in the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD) and are generalized based on metabolic logic. The predictive accuracy of the PPS was tested: (1) using a 113-member set of compounds found in the database, (2) against a set of compounds whose metabolism was predicted by human experts, and (3) for consistency with experimental microbial growth studies. First, the system correctly predicted known metabolism for 111 of the 113 compounds containing C and H, O, N, S, P and/or halides that initiate existing pathways in the database, and also correctly predicted 410 of the 569 known pathway branches for these compounds. Second, computer predictions were compared to predictions by human experts for biodegradation of six compounds whose metabolism was not described in the literature. Third, the system predicted reactions liberating ammonia from three organonitrogen compounds, consistent with laboratory experiments showing that each compound served as the sole nitrogen source supporting microbial growth. The rule-based nature of the PPS makes it transparent, expandable, and adaptable.

Bacteria↗

PubMed2001

Pathogenicity islands: the tip of the iceberg.

Pathogenicity islands represent distinct genetic elements encoding virulence factors of pathogenic bacteria. Pathogenicity islands belong to the class of genomic islands, which are common genetic elements sharing a set of unifying features. Genomic islands have been acquired by horizontal gene transfer. In recent years many different genomic islands have been discovered in a variety of pathogenic as well as non-pathogenic bacteria. Because they promote genetic variability, genomic islands play an important role in microbial evolution.

Animals↗

PubMed2026

Ferroptosis as a mediator of gut microbiota-driven inflammatory bowel disease: Evidence from genetic analyses.

Gut microbiota dysbiosis is increasingly recognized as a contributor to inflammatory bowel disease (IBD), yet causal relationships and underlying mechanisms remain unclear. Ferroptosis, an iron-dependent form of regulated cell death, plays a key role in epithelial barrier damage and inflammation. This study aimed to determine whether specific gut microbial taxa are causally associated with IBD and whether ferroptosis-related genes mediate this association using Mendelian randomization (MR). Two-sample MR and mediation MR analyses were performed using genome-wide association study summary data from the FinnGen consortium (IBD), the genome-wide association study catalog (473 gut microbial taxa), and the deCODE database (ferroptosis-related genes). Instrumental variables were selected with thresholds of P < 1 × 10-6 for microbes and P < 5 × 10-8 for traits, and linkage disequilibrium clumping (r2 < 0.001) was applied. Twenty-three microbial taxa showed significant causal associations with IBD (e.g., Chromatiales, OR = 0.51; Acetobacterales, OR = 2.61). Several ferroptosis-related genes were linked to IBD risk (e.g., GPX4, STAT3, IDO1). Mediation MR revealed that genes such as MUC1, IDO1, and ADAM23 partially mediated microbial effects on IBD, with mediation proportions up to 7.6%. This study provides novel genetic evidence supporting a gut microbiota-ferroptosis-IBD axis. Ferroptosis-related pathways may partially mediate microbial effects on IBD pathogenesis and represent promising targets for future therapeutic interventions.

Ferroptosis↗

PubMed2025

Seq2Saccharide: Discovering Oligosaccharides and Aminoglycosides Natural Products by Integrating Computational Mass Spectrometry and Genome Mining.

Natural oligosaccharides and aminoglycosides are important sources of new drug candidates, especially in the development of antibiotics. In the past, discovering novel saccharides has been time-consuming and costly. However, the rapid expansion of high-throughput data, including genomic and mass spectrometry data sets, has greatly increased opportunities for natural saccharide discovery. Yet, due to the complex biosynthesis pathways of saccharides, no existing method can predict their structures with high precision. To address this, we introduce Seq2Saccharide, a tool designed to automate saccharide natural product discovery by integrating both genomic and mass spectrometry data. To enhance accuracy, Seq2Saccharide predicts hundreds or thousands of putative structures for each gene cluster. The correct structure is then identified from these predictions using a mass spectral search. Benchmarks against saccharides in the MiBIG database show that Seq2Saccharide outperforms existing methods in predicting the structure of saccharides. Furthermore, mass spectrometry analysis indicates that the variable search module can correct mispredictions from genome mining. By searching genomic and mass spectrometry data of microbial strains, Seq2Saccharide correctly identified the biosynthetic gene cluster for the polysaccharide oligosaccharide trestatin B.

Aminoglycosides↗

PubMed2001

Complete genomic sequence of Pasteurella multocida, Pm70.

We present here the complete genome sequence of a common avian clone of Pasteurella multocida, Pm70. The genome of Pm70 is a single circular chromosome 2,257,487 base pairs in length and contains 2,014 predicted coding regions, 6 ribosomal RNA operons, and 57 tRNAs. Genome-scale evolutionary analyses based on pairwise comparisons of 1,197 orthologous sequences between P. multocida, Haemophilus influenzae, and Escherichia coli suggest that P. multocida and H. influenzae diverged approximately 270 million years ago and the gamma subdivision of the proteobacteria radiated about 680 million years ago. Two previously undescribed open reading frames, accounting for approximately 1% of the genome, encode large proteins with homology to the virulence-associated filamentous hemagglutinin of Bordetella pertussis. Consistent with the critical role of iron in the survival of many microbial pathogens, in silico and whole-genome microarray analyses identified more than 50 Pm70 genes with a potential role in iron acquisition and metabolism. Overall, the complete genomic sequence and preliminary functional analyses provide a foundation for future research into the mechanisms of pathogenesis and host specificity of this important multispecies pathogen.

Base Sequence↗

PubMed2026

Metax enables accurate cross-domain taxonomic profiling of metagenomes.

Taxonomic profiling is fundamental to microbiome research, yet achieving high species-level accuracy remains challenging for complex communities that span bacteria, viruses, eukaryotes, and archaea, and these limitations are exacerbated in low-biomass, host-dominated samples. We introduce Metax, a cross-domain taxonomic profiler that integrates coverage-based probabilistic modeling with an expectation-maximization framework to distinguish true microbial signals from artifacts. Across >600 samples from host-associated, environmental, wastewater, and low-biomass clinical settings, including benchmarks with limited reference representation, Metax improved profiling accuracy, achieving on average 55% higher F1 scores and 45% lower Bray-Curtis dissimilarity than other methods. Moreover, this broad evaluation demonstrated that Metax resolved bacterial and viral signatures of peri-implantitis in oral microbiomes and revealed signals suggestive of reagent-borne contaminants and reference misassemblies in plasma-cell-free DNA. By leveraging genome-wide coverage evidence, Metax enables robust cross-domain profiling across diverse sample types and sequencing depths, including settings where reference databases are highly incomplete.

abundance estimation↗

PubMed2001

Mosaic genes and mosaic chromosomes: intra- and interspecies genomic variation of Streptococcus pneumoniae.

Streptococcus pneumoniae remains a major causative agent of serious human diseases. The worldwide increase of antibiotic resistant strains revealed the importance of horizontal gene transfer in this pathogen, a scenario that results in the modulation of the species-specific gene pool. We investigated genomic variation in 20 S. pneumoniae isolates representing major antibiotic-resistant clones and 10 different capsular serotypes. Variation was scored as decreased hybridization signals visualized on a high-density oligonucleotide array representing 1,968 genes of the type 4 reference strain KNR.7/87. Up to 10% of the genes appeared altered between individual isolates and the reference strain; variability within clones was below 2.1%. Ten gene clusters covering 160 kb account for half of the variable genes. Most of them are associated with transposases and are assumed to be part of a flexible gene pool within the bacterial population; other variable loci include mosaic genes encoding antibiotic resistance determinants and gene clusters related to bacteriocin production. Genomic comparison between S. pneumoniae and commensal Streptococcus mitis and Streptococcus oralis strains indicates distinct antigenic profiles and suggests a smooth transition between these species, supporting the validity of the microarray system as an epidemiological and diagnostic tool.

Alleles↗

PubMed2024

A comparative genomic study of a hydrocarbon-degrading marine bacterial consortium.

Ocean oil pollution has a large impact on the environment and the health of living organisms. Bioremediation cleaning strategies are promising eco-friendly alternatives for tackling this problem. Previously, we designed and reported a hydrocarbon (HC) degrading microbial consortium of four marine strains belonging to the species Alloalcanivorax xenomutans, Halopseudomonas aestusnigri, Paenarthrobacter sp., and Pseudomonas aeruginosa. However, the knowledge about the metabolic potential of this bacterial consortium for HC bioremediation is not yet well understood. Here, we analyzed the complete genomes of these marine bacterial strains accompanied by a phylogenetic reconstruction along with 138 bacterial strains. Synteny between complete genomes of the same species or genus, revealed high conservation among strains of the same species, covering over 91% of their genomic sequences. Functional predictions highlighted a high abundance of genes related to HC degradation, which may result in functional redundancy within the consortium; however, unique and complete gene clusters linked to aromatic degradation were found in the four genomes, suggesting substrate specialization. Pangenome gain and loss analysis of genes involved in HC degradation provided insights into the evolutionary history of these capabilities, shedding light on the acquisition and loss of relevant genes related to alkane and aromatic degradation. Our work, including comparative genomic analyses, identification of secondary metabolites, and prediction of HC-degrading genes, enhances our understanding of the functional diversity and ecological roles of these marine bacteria in crude oil-contaminated marine environments and contributes to the applied knowledge of bioremediation.

Biodegradation, Environmental↗

PubMed2026

Host-independent metagenomics reveal gut bacteria contribution to Delia antiqua growth by vitamin B6 provision.

Insect guts host a diverse and abundant array of microorganisms. These microbes improve host fitness by extensively involving in a range of crucial physiological processes, which have mainly been revealed by high-throughput sequencing, particularly metagenomics. However, it is almost impossible to make an accurate and complete distinction between the genetic functions of microbial symbionts and insect hosts without host genome data. By comparing metagenomic data from gut germ-free and nonaxenic larvae, we accurately identified the data belonging to the gut microbiome of the onion maggot Delia antiqua (Diptera: Anthomyiidae). Besides, a correlation between bacteria of the genus Wohlfahrtiimonas (Gammaproteobacteria: Pseudomonadaceae) and vitamin B6 metabolism was detected through collinearity analysis. Furthermore, in vitro tests confirmed that the gut bacterium Wohlfahrtiimonas larvae contributed to the growth of D. antiqua larvae via the independent synthesis of vitamin B6. This study provides a comprehensive view of the gut bacterial diversity in D. antiqua and reveals a functional profile that is strictly specific to the gut microbiota of this species. It has preliminarily revealed the functional differentiation between insect hosts and their symbiotic microorganisms. This study also offers a technical reference for the study of microbial symbiotic functions in other insect-microbe symbioses without host genomic data.

Animals↗

PubMed2025

Comparative genomics of carbapenem-resistant Acinetobacter baumannii isolated from pediatric patients in a tertiary care hospital.

Acinetobacter baumannii is a short gram-negative bacillus, notable for its intrinsic multidrug resistance and genomic plasticity, which facilitates the acquisition of additional resistance genes via mobile genetic elements. Due to its increasing carbapenem resistance, the World Health Organization has classified it as a critical priority pathogen. This study performed a comparative genomic analysis of 20 carbapenem-resistant A. baumannii clinical strains isolated from the Hospital Infantil de México Federico Gómez (CRAB-HIMFG), alongside 11 genomes from other Mexican strains. The pangenome was determined to be open, and core genome single-nucleotide polymorphism-based analysis grouped the CRAB-HIMFG strains within CC758/IC5 and CC92/IC2. A novel sequence type (ST) in the MLST-Pasteur scheme was identified, related to STPas156, and in the MLST-Oxford scheme, associated with STOxf758 and STOxf1054. Virulence and resistance genes comprised 0.61% to 2.23% of the pangenome. Oxacillinase genes and efflux pumps primarily mediated carbapenem resistance, while virulence genes included those encoding biofilm and type IV pili. Capsule typing revealed a correlation with established international clones, IC2 and IC5. Plasmids exhibited high diversity, harboring maintenance modules and toxin-antitoxin systems, with the dissemination of resistance genes linked to insertion sequences. Biofilm formation and twitching motility were not always expressed, as they depend on additional environmental factors. Our study shows that comparative genomics is an essential tool to analyze clinically and epidemiologically significant genomes, providing critical insights into gene distribution, genomic architecture, and horizontal gene transfer mechanisms in microbial populations.IMPORTANCEIn recent years, a reported increase in the mortality rate associated with infections caused by A. baumannii, along with a rise in carbapenem resistance, poses a serious clinical challenge. The WHO considered this microorganism critical for research into alternative therapies and epidemiological surveillance. Despite advances in bioinformatics, genomic studies have yet to fully elucidate the structural rearrangements and secretion systems of A. baumannii. This knowledge gap hinders our understanding of its remarkable genomic plasticity and its ability to acquire and spread resistance and virulence genes through horizontal gene transfer.

Acinetobacter baumannii↗

PubMed2006

Pathogenicity islands: a molecular toolbox for bacterial virulence.

Pathogenicity islands (PAIs) are distinct genetic elements on the chromosomes of a large number of bacterial pathogens. PAIs encode various virulence factors and are normally absent from non-pathogenic strains of the same or closely related species. PAIs are considered to be a subclass of genomic islands that are acquired by horizontal gene transfer via transduction, conjugation and transformation, and provide 'quantum leaps' in microbial evolution. Data based on numerous sequenced bacterial genomes demonstrate that PAIs are present in a wide range of both gram-positive and gram-negative bacterial pathogens of humans, animals and plants. Recent research focused on PAIs has not only led to the identification of many novel virulence factors used by these species during infection of their respective hosts, but also dramatically changed our way of thinking about the evolution of bacterial virulence.

Bacteria↗

PubMed2000

Rapid identification of Pseudomonas aeruginosa from ocular isolates by PCR using exotoxin A-specific primers.

The purpose of this research was to evaluate the use of PCR for the identification of ocular isolates of Pseudomonas aeruginosa by using primers specific to the exotoxin A gene of the bacteria. Genomic DNA was obtained from ocular microbial isolates of keratitis patients. Primers were designed based on the published sequence of the exotoxin A gene of P. aeruginosa. Using the primers designed, PCR reactions were performed on the DNA samples. The PCR was also examined for its specificity and sensitivity. In addition, a direct PCR using heating method was attempted on P. aeruginosa with no separate DNA extraction step. ATCC strains of P. aeruginosa were included as positive controls. The rest of the bacteria other than P. aeruginosa served as negative controls. A single band was obtained when analysed on agarose gel electrophoresis only from samples that contained genomic DNA of P. aeruginosa. The direct PCR method was also successful with the same band produced from the amplification. The whole process was completed within 4 h. The direct PCR amplification targeting at the exotoxin A gene of P. aeruginosa is potentially a rapid, specific, sensitive and relatively simple method for the identification of ocular isolates of P. aeruginosa.

ADP Ribose Transferases↗

PubMed1998

[Update on hepatitis C virus: its variability and the implications].

Hepatitis C virus (HCV) is the main etiologic factor of post-transfusional and sporadic hepatitis, called non-A non-B in the past. These infections are characterized by a very high number of chronic carriers always with a persistent viral increase, but often at a slow pace. The seriousness of liver disease differs from one individual to another, varying from an asymptomatic form with minor or no liver injuries, to cirrhosis and hepatocellular carcinoma. Physiopathological mechanisms involved in liver injuries are still poorly understood. The direct role of immune response and of possible genetic factors is still under study. This review aims at summing up the discovery of HCV, its structure, and its variability in the various genome regions in the same individual and from one individual to another. The different methods and techniques to analyze this variability are also reviewed, as well as the various suggested ways of classifying the different types. The geographical distribution and both clinical and biological consequences of this variability are also discussed.

Antibody Specificity↗