Biology subjects

Szafranski, S. P.

Publications and source records attributed to Szafranski, S. P..

4 recordsLinked to original sources

bioRxiv2025

High-resolution taxonomic profiling and metatranscriptomics identify microbial, biochemical, host and ecological factors in peri-implant disease

Biofilm-associated diseases like peri-implant mucositis (PIM) and peri-implantitis (PI) are significant clinical challenges affecting millions of dental implant patients globally. Although studies have described the role of microbial, host, or environmental factors in disease development, their complex interplay, particularly during dysbiosis remains poorly understood. This cross-sectional study characterized the microbiome composition and metatranscriptomes of 125 peri-implant biofilms from 48 individuals uncovering molecular signatures linked to peri-implant health (PIH), PIM, and PI. Distinct variations were observed in biofilm amount, composition, activity, phage populations and host response. Biofilms were categorized into four community types (CTs) based on the bacterial transcriptional activity: one linked to PIH, one to PI, and two to PIM. PIH and PIM were primarily characterized by aerotolerant taxa with increased anabolic processes, while PI was dominated by obligate anaerobes with complex biofilm morphology, and heightened catabolic activity and virulence. PIM samples, relative to PIH were characterized by biofilm expansion with minimal functional changes, except for the Neisseria-rich PIM subtype showing higher pyruvate and lipoic acid metabolism. The phagome mirrored the bacterial compositional variations across disease states. Furthermore, human transcriptome responses varied indicating increased keratinization in PIH, enhanced expression of ribosome components in PIM, and inflammatory signaling and hypoxia in PI. Additionally, we identified complex species-enzyme, phage-bacteria, and host-microbe associations within the peri-implant ecosystem. Our integrative multi-omics approach provides a comprehensive view of microbial, biochemical, host, and ecological factors associated with dysbiosis, offering novel insights into peri-implant disease dynamics. ImportancePeri-implant mucositis and peri-implantitis are highly prevalent inflammatory conditions that compromise the long-term survival and success of dental implants, yet their underlying biological mechanisms are largely unresolved. While next-generation sequencing has advanced our understanding of microbial composition across health and peri-implant diseases, it falls short of capturing microbial activity and the broader molecular context of peri-implant dysbiosis. Metatranscriptomics overcomes this limitation by profiling actively transcribed genes within the biofilm, offering direct insights into microbial community functions. In this study, we integrated full-length 16S rRNA gene amplicon sequencing with metatranscriptomic profiling to simultaneously assess microbial taxonomy, functional activity, phage dynamics, and host gene expression in peri-implant biofilms. Importantly, we provide a systems-level view and report previously undescribed associations between different molecular signatures in peri-implant ecosystem.

microbiology↗

bioRxiv2025

Invasive species drive polymicrobial resistance to amoxicillin in oral biofilms through beta-lactamase release

Since bacterial biofilms often cause refractory infections, antimicrobial susceptibility testing (AST) is highly desirable even for oral peri-implant biofilms. However, characterization of polymicrobial drug resistance is challenging due to high diversity and complexity of these biofilms. In this work, we developed laser-assisted AST and detected polymicrobial amoxicillin resistance in peri-implantitis. TEM-1 {beta}-lactamase production enabled an Enterobacter sp. strain SPS_532 to protect its otherwise susceptible biofilm cohabitants. To understand the {beta}-lactamase driven cross-protection in the human microbiome we aggregated genomic (n = 200,000) and patient microbial data (n = 27,000), developed a cross-protection assay, studied a representative strain collection (n = 118) and established a complex biofilm in vitro model (with an average of 133 species from 164 found in dental plaque). Multiple oral allochthonous species, e.g., Enterobacter, Klebsiella, Escherichia, Staphylococcus, and only a single typical oral microorganism, Haemophilus, were able to cross-protect. Diverse bla genes conferred activity, via a high expression of chromosomal gene, e.g., blaAmpC gene or by the presence of plasmidic gene, e.g., blaTEM-1 gene. Invaders not only cross-protected the biofilm from the antibiotic, but also supported expansion of opportunistic pathogens like Fusobacterium species. Cross-protection in complex biofilms depended on the diffusion rate and population size of the invader, which could be bio-controlled with a phage. Deciphering polymicrobial resistance might support the development of diagnostic and therapeutic approaches to combat implant-associated biofilm infections in the human mouth.

microbiology↗

bioRxiv2025

Integrative microbiome- and metatranscriptome-based analyses reveal diagnostic biomarkers for peri-implantitis

Peri-implantitis is a severe biofilm-associated infection of the tissues around dental implants that increases the risk of implant failure. The prognosis of peri-implantitis treatment is compromised by the resistance of well-organized and mature bacterial biofilms. Thus, early diagnosis of a pathogenic biofilm would enable treatment at a prognostically favourable stage. However, relatively little is known about how the microbial constitution of the biofilm changes during disease development. The aim of this cross-sectional study was therefore to identify peri-implant taxonomic and functional biomarkers that reliably indicate peri-implantitis using paired data from full length 16S rRNA gene amplicon sequencing (full-16S) and metatranscriptomics (RNAseq). Disease signatures were identified using 24 healthy and 24 peri-implantitis-associated biofilm samples from 32 patients. The taxonomic measurements were validated with 68 additional full-16S samples from another 40 patients. Both full-16S and RNAseq revealed significant differences between healthy and peri-implantitis samples, with respect to both the microbiome and functional profiles. A shift from aerotolerant Gram-positive bacteria to anaerobic Gram-negative bacteria was observed in peri-implantitis. Distinct metabolic pathways were expressed in healthy and peri-implantitis samples. Our results, based on paired taxonomic and functional profiles, provide for the first time important insights into the complex peri-implant biofilm ecology related to amino acid metabolism. Integrating taxonomic and functional information improved the predictive ability (AUC = 0.85) of the machine learning models and revealed diagnostic biomarkers with large effect sizes (Cohens d > 0.8). Primary biomarkers included health-associated Streptococcus, Rothia species and enzymes associated with peri-implantitis (urocanate hydratase, tripeptide aminopeptidase, NADH:ubiquinone reductase, phosphoenolpyruvate carboxykinase and polyribonucleotide nucleotidyltransferase - mostly expressed by Fusobacteriia and Bacteroidia). Thus, biofilm profiling at these two molecular levels reveals highly predictive disease biomarkers and provide the basis for developing early diagnostics and individualized therapy approaches for peri-implant diseases.

microbiology↗

bioRxiv2025

Biofilm development of Porphyromonas gingivalis on titanium surfaces in response to 1,4-dihydroxy-2-naphthoic acid - a hybrid in vitro - in silico approach

Colonization of titanium dental implants by the oral pathogen Porphyromonas gingivalis can lead to peri-implant diseases and, ultimately, implant failure. P. gingivalis growth can be stimulated by 1,4-dihydroxy-2-naphthoic acid (DHNA), a menaquinone precursor from various oral bacteria, yet its impact on biofilm formation remains unclear. The aim of the study was to evaluate P. gingivalis growth and metabolic activity over six days in response to DHNA on two titanium grade IV surfaces with different roughness using a hybrid in vitro - in silico approach. P. gingivalis growth was modestly stimulated by DHNA and exhibited an inverse correlation with ammonia concentration in culture medium. Notably, this growth pattern transitioned from an initial linear phase to a later exponential phase, with DHNA-treated biofilms reaching this exponential shift at an earlier stage than untreated controls. Confocal microscopy revealed that DHNA-treated biofilms exhibited surface-dependent growth patterns, with larger biofilm volumes observed on rougher surfaces in later biofilm stages, compared to smoother surfaces. Regardless of surface characteristics, the area occupied by biofilms and the size of the aggregates exhibited a consistent and progressive increase over time and was larger in late DHNA-treated biofilms. The experimental data were used to calibrate a coupled finite element method (FEM)-based model that simulated P. gingivalis biofilm dynamics and nutrient utilization. Summarizing, DHNA moderately stimulated P. gingivalis growth, accelerated its transition to ammonia-independent growth, and promoted an increase in biofilm area and aggregate size. Our coupled approach offers significant potential for advancing in vitro biofilm research. ImportanceResults of our hybrid in vitro - in silico experiments advance the research on P. gingivalis physiology and its DHNA-dependent colonization of implant surfaces. Our findings reveal that DHNA accelerates P. gingivalis growth, induces aggregation and promotes colonization of titanium surfaces. For the first time, DHNA-induced P. gingivalis growth acceleration and an earlier shift away from ammonia dependency were observed fluorometrically, highlighting ammonia assimilation as a promising marker of P. gingivalis physiology during early biofilm expansion. Understanding how growth factors together with surface properties influence P. gingivalis colonization offers a basis for future preventive strategies. Our studys stringent characterization of 3D surface texture parameters is expected to improve reproducibility of biofilm-surface interactions experiments. The findings were validated using a continuum-based in silico model, initiating a hybrid approach where computational models complement in vitro research. Our interdisciplinary approach offers a versatile framework for investigating additional aspects of oral biofilms on titanium.

microbiology↗