Antibiotic tolerance among clinical isolates: mechanisms, detection, prevalence, and significance.

SUMMARYAntibiotic treatment failures in the absence of resistance are not uncommon. Recently, attention has grown around the phenomenon of antibiotic tolerance, an underappreciated contributor to recalcitrant infections first detected in the 1970s. Tolerance describes the ability of a bacterial population to survive transient exposure to an otherwise lethal concentration of antibiotic without exhibiting resistance. With advances in genomics, we are gaining a better understanding of the molecular mechanisms behind tolerance, and several studies have sought to examine the clinical prevalence of tolerance. Attempts have also been made to assess the clinical significance of tolerance through in vivo infection models and prospective/retrospective clinical studies. Here, we review the data available on the molecular mechanisms, detection, prevalence, and clinical significance of genotypic tolerance that span ~50 years. We discuss the need for standardized methodology and interpretation criteria for tolerance detection and the impact that methodological inconsistencies have on our ability to accurately assess the scale of the problem. In terms of the clinical significance of tolerance, studies suggest that tolerance contributes to worse outcomes for patients (e.g., higher mortality, prolonged hospitalization), but historical data from animal models are varied. Furthermore, we lack the necessary information to effectively treat tolerant infections. Overall, while the tolerance field is gaining much-needed traction, the underlying clinical significance of tolerance that underpins all tolerance research is still far from clear and requires attention.

Easy analysis of bacterial whole-genome sequencing data for clinical microbiologists using open-source Galaxy Platform: characterization of ESBL-producing Enterobacterales from bloodstream infections.

OBJECTIVES: Clinical microbiologists require easy-to-use open access tools with graphical interfaces to perform bacterial whole-genome sequencing (WGS) in routine practice. This study aimed to build a bioinformatics pipeline on the open-source Galaxy platform, facilitating comprehensive and reproducible analysis of bacterial WGS data in a few steps. We then used it to characterize our local epidemiology of ESBL-producing Enterobacterales isolated from patients with bacteremia. METHODS: We built a bioinformatics pipeline consisting of the following sequential tools: Fastp (input data trimming); FastQC (read quality control); SPAdes (genome assembly); Quast (quality control of genome assembly); Prokka (gene annotation); Staramr (ResFinder database) and ABRicate (CARD database) for antimicrobial resistance (AMR) gene screening and molecular strain typing. Paired-end short read WGS data from all ESBL-producing Enterobacterales strains isolated from patients with bacteremia over one year were analyzed. RESULTS: The Galaxy platform does not require command line tools. The bioinformatics pipeline was constructed within one hour. It only required uploading fastq files and facilitated systematization of the de novo assembly of genomes, MLST typing, and AMR gene screening in one step. Among the 66 ESBL-producing strains analyzed, the two most frequent ESBL genes were blaCTX-M-15 (62.1 %) and blaCTX-M-27 (13.6 %). CONCLUSIONS: The open-access Galaxy platform provides a graphical interface and easy-to-use tools suitable for routine use in clinical microbiology laboratories without bioinformatics specialists. We believe that this platform will facilitate fast and low-cost analysis of bacterial WGS data, especially in resource-limited settings.

Simulation to optimize the laboratory diagnosis of bacteremia.

Blood cultures are central to the management of patients with sepsis and bloodstream infection. Clinical decisions depend on the timely availability of laboratory information, which, in turn, depends on the optimal laboratory processing of specimens. Discrete event simulation (DES) offers insights into where optimization efforts can be targeted. Here, we generate a detailed process map of blood culture processing within a laboratory and use it to build a simulator. Direct observation of laboratory staff processing blood cultures was used to generate a flowchart of the blood culture laboratory pathway. Retrospective routinely collected data were combined with direct observations to generate probability distributions over the time taken for each event. These data were used to inform the DES model. A sensitivity analysis explored the impact of staff availability on turnaround times. A flowchart of the blood culture pathway was constructed, spanning labeling, incubation, organism identification, and antimicrobial susceptibility testing. Thirteen processes in earlier stages of the pathway, not otherwise captured by routinely collected data, were timed using direct observations. Observations revealed that specimen processing is predominantly batched. Another eight processes were timed using retrospective data. A simulator was built using DES. Sensitivity analysis revealed that specimen progression through the simulation was especially sensitive to laboratory technician availability. Gram stain reporting time was also sensitive to laboratory scientist availability. Our laboratory simulation model has wide-ranging applications for the optimization of laboratory processes and effective implementation of the changes required for faster and more accurate results. IMPORTANCE: Optimization of laboratory pathways and resource availability has a direct impact on the clinical management of patients with bloodstream infection. This research offers an insight into the laboratory processing of blood cultures at a system level and allows clinical microbiology laboratories to explore the impact of changes to processes and resources.

Microbiological Profiles of the Anatomical Sites of Perforation Peritonitis: A Cross-Sectional Study.

Introduction One of the most frequent emergencies that a general surgeon deals with is perforation peritonitis. The anatomical site of the perforation, which in turn affects the source of infection, has a major impact on the mortality rate due to perforation peritonitis. Early and suitable antibiotic therapy can be started in the postoperative period with the aid of knowledge about the microbiological profile and sensitivity of peritoneal fluid culture with respect to the anatomical sites of perforation peritonitis. Methods A cross-sectional study was conducted from June 2021 to November 2021 where peritoneal fluid samples were collected intraoperatively from patients with perforation peritonitis. This was subjected to culture and sensitivity, and results were analyzed with respect to anatomical sites of perforation. Results Forty cases were investigated. The ileum (30%) was the most common site of perforation, followed by the stomach (22.5%), appendix (20%), duodenum (12.5%), caecum (5%), jejunum (5%), transverse colon (2.5%), and rectum (2.5%). Escherichia coli (E. coli) and Klebsiella spp. were the most frequently found organisms in all sites of perforation peritonitis. The most sensitive antibiotics covering all isolated organisms were amikacin and meropenem. Sensitivity to amikacin was found in 85.18% of cases of E. coli and 84.6% of cases of Klebsiella. Sensitivity to meropenem was found in 76.9% of cases of E. coli and 80% of cases of Klebsiella. Conclusion In patients with perforation peritonitis, the peritoneal fluid cultures did not reflect the major differential normal flora according to the region of the gastrointestinal tract. The most prevalent organism isolated among all the sites of perforation peritonitis was E. coli. Antimicrobial activity against organisms isolated from perforation peritonitis patients was significantly demonstrated by aminoglycosides, piperacillin and tazobactam, and meropenem and colistin, with considerable resistance to third-generation cephalosporins.

Potential roles for artificial intelligence in clinical microbiology from improved diagnostic accuracy to solving the staffing crisis.

OBJECTIVES: This review summarizes the current and potential uses of artificial intelligence (AI) in the current state of clinical microbiology with a focus on replacement of labor-intensive tasks. METHODS: A search was conducted on PubMed using the key terms clinical microbiology and artificial intelligence. Studies were reviewed for relevance to clinical microbiology, current diagnostic techniques, and potential advantages of AI in routine microbiology workflows. RESULTS: Numerous studies highlight potential labor, as well as diagnostic accuracy, benefits to the implementation of AI for slide-based and macroscopic digital image analyses. These range from Gram stain interpretation to categorization and quantitation of culture growth. CONCLUSIONS: Artificial intelligence applications in clinical microbiology significantly enhance diagnostic accuracy and efficiency, offering promising solutions to labor-intensive tasks and staffing shortages. More research efforts and US Food and Drug Administration clearance are still required to fully incorporate these AI applications into routine clinical laboratory practices.

A Microbiology Analytics Tool to Evaluate the Burden of Antibiotic-Resistant Infections.

Leveraging the capabilities of a microbiological clinical analytics tool, this study delves into quantifying the public health impact of antibiotic-resistant bacteria. Focusing on eight predominant antibiotic-resistant bacteria, the study utilizes University Hospital Vienna's data to calculate the burden of antibiotic-resistant infections in disability-adjusted life years. The results highlight the potential of extended analytics tools in epidemiological research and underscore the pressing challenge of antimicrobial drug resistance.

MALDI-TOF direct identification of positive blood cultures: A four-year analytical evaluation of A Triton based workflow.

Rapid and reliable identification of the causal organism in bloodstream infections and sepsis is crucial for both individual patient care and public health. We have implemented a rapid in-house identification protocol (with 10 % Triton) using MALDI-TOF MS for identifying the causative organism in positive blood cultures without prior culture. Our objective was to retrospectively analyze data collected over a four-year period while implementing this rapid in-house identification protocol and to develop a guide for evaluating and reporting the obtained results. Overall, our method utilizing MALDI-TOF MS for rapid in-house identification, demonstrated comparable results to other commercially available and in-house methods reported in the literature. Over the past four years, direct identification has facilitated the distinction between clinically relevant positive blood cultures and irrelevant ones, guiding rapid focus control and appropriate antibiotic treatment. The established guide can serve as a valuable tool in reporting positive blood cultures and associated antibiotic treatments.

Scientific misconduct in infectious diseases-European Society of Clinical Microbiology and Infectious Diseases survey.

OBJECTIVES: We aimed to evaluate the prevalence and perception of scientific misconduct in infectious diseases (ID) and clinical microbiology (CM), as reported by the ID/CM community. METHODS: An anonymous online European Society of Clinical Microbiology and Infectious Diseases survey circulated among society members from October 2023 to June 2024; the questionnaire included data on participants' views on their own and their colleagues' scientific misconduct in the last 5 years. RESULTS: The survey received 220 responses. Responders were 73% ID physicians, 52% men, 56% aged 35-54 years, and represented 48 countries, mainly European (126 participants). The vast majority of participants (78%) reported that they did not personally commit scientific misconduct, whereas 54% reported witnessing misconduct by colleagues in their field. The most commonly committed misconduct by both responders and their colleagues was misconduct of authorship rules, 14% and 41%, respectively. Overall, 18% reported witnessing misleading reporting and 14% reported witnessing nonaccurate reporting of conflict of interest. Nevertheless, the majority (>60%) of responders reported high confidence in the integrity of published work in the field of ID/CM. Approximately one-third of responders were not aware of the European Society of Clinical Microbiology and Infectious Diseases ethics advisory committee as an authority to which members can report misconduct. DISCUSSION: Scientific misconduct, mostly related to violation of authorship rules, seems to be common in ID/CM. Efforts to improve scientific integrity should be made to keep trust in the scientific process.

Candida spp.: the burden of a microorganism in a microbiology department.

There is no precise information available on the entire workload of isolating a specific microorganism in a clinical microbiology laboratory, and the costs associated with it have not been specifically estimated. In this descriptive retrospective study conducted at the microbiology department of a general teaching hospital from January 2021 to December 2022, we assessed the workload associated with identifying Candida species in all types of clinical samples and patients. Costs were estimated from data obtained from the hospital's finance department and microbiology laboratory cost records. In 2 years, 1,008,231 samples were processed at our microbiology department, of which 8,775 had one or more Candida spp. isolates (9,683 total isolates). Overall, 5,151 samples with Candida spp. were identified from 2,383 inpatients. We isolated Candida spp. from 515.3 samples/100,000 population/year and from 92 samples/1,000 hospital admissions/year. By sample type, 90.8% were superficial, mainly mucosal. Only 9.1% Candida spp. were isolated from deep, usually sterile, samples, being mostly from ordinarily sterile fluids. Candida albicans was the main species (58.5%) identified, followed by C. parapsilosis complex, C. glabrata, C. tropicalis, and C. krusei. In admitted patients, the incidences of samples with Candida spp. isolates were 302.7 samples/100,000 population/year and 54 samples/1,000 admissions/year. The average cost of isolating and identifying Candida spp. was estimated at 25€ per culture-positive sample. To our knowledge, this is the first attempt to gage the workload and costs of Candida spp. isolation at a hospital microbiology department. These data can help assess the burden and significance of Candida isolation at other institutions and also help design measures for streamlining. IMPORTANCE: We believe that this work is of interest because at present, there is no really accurate information available on the total workload involved in isolating a specific microorganism in a clinical microbiology laboratory. The costs related to this have also not been described. We have described the unrestricted workload of Candida spp. in all types of samples for all types of species and patients. We believe that this information would be necessary to collect and share this information as well as to collect it in a standardized way to know the current situation of Candida spp. workload in all clinical microbiology laboratories.

A summary of the main themes and findings presented at the ASM Intermountain Branch meeting (2024).

The annual meeting for the Intermountain Branch was held in April 2024 on the campus of Brigham Young University. There were 127 branch members from Utah, Idaho, and Nevada who attended the meeting and were composed of undergraduate students, graduate or medical students, and faculty. This report highlights the diversity of, and the emerging trends in, the research conducted by American Society for Microbiology members in the Intermountain Branch.

Diagnostic Stewardship in Clinical Microbiology: An Indispensable Component of Patient Care.

Emerging infectious diseases and increasing resistance to available antimicrobials are mapping the evolution of clinical microbiology and escalating the nature of undertakings required. Rapid diagnosis has become the need of the hour, which can affect diagnostic algorithms and therapeutic decisions simultaneously. Subsequently, the concept of 'diagnostic stewardship' was introduced into clinical practice for coherent implementation of available diagnostic modalities to ensure that these new rapid diagnostic technologies are conserved, rather than consumed as part of health care resources, with a view to improve the patient care and reduce Turnaround Time (TAT) and treatment expense. The present study highlights the requisite of diagnostic stewardship and outlines the infectious disease diagnostic modalities that can assist in its successful implementation. Diagnostic stewardship promotes precise, timely diagnostics, from the initial specimen collection and identification to reporting with appropriate TAT, so as to enable timely management of the patient. The main aim of diagnostic stewardship is to optimize the right choice of diagnostic test for the right patient to attain clinically significant reports with the least possible TAT for timely management and the least expected adverse effects for the patient, community, and the healthcare system. This underlines the requisite of a multifaceted approach to make technological advancements effective and successful for implementation as a part of diagnostic stewardship for the best patient care.

The bacterial and fungal profiles of patients hospitalized with non-COVID-19 lower respiratory tract infections in Wuhan, China, 2019-2021.

AIMS: A severe lockdown occurred in Wuhan during the COVID-19 pandemic, followed by a remission phase in the pandemic's aftermath. This study analyzed the bacterial and fungal profiles of respiratory pathogens in patients hospitalized with non-COVID-19 lower respiratory tract infections (LRTIs) during this period to determine the pathogen profile distributions in different age groups and hospital departments in Wuhan. METHODS AND RESULTS: We collected reports of pathogen testing in the medical records of patients hospitalized with non-COVID-19 LRTI between 2019 and 2021. These cases were tested for bacterial and fungal pathogens using 16S and internal transcribed spacer sequencing methods on bronchoalveolar lavage fluid samples. The study included 1368 cases. The bacteria most commonly identified were Streptococcus pneumoniae (12.50%) and Mycoplasma pneumoniae (8.33%). The most commonly identified fungi were Aspergillus fumigatus (2.49%) and Pneumocystis jirovecii (1.75%). Compared to 2019, the S. pneumoniae detection rates increased significantly in 2021, and those of M. pneumoniae decreased. Streptococcus pneumoniae was detected mainly in children. The detection rates of almost all fungi were greater in the respiratory Intensive Care Unit compared to respiratory medicine. Streptococcus pneumoniae and M. pneumoniae were detected more frequently in the pediatric department. CONCLUSIONS: Before and after the COVID-19 outbreak, a change in the common pathogen spectrum was detected in patients with non-COVID-19 in Wuhan, with the greatest change occurring among children. The major pathogens varied by the patient's age and the hospital department.

Defining the value of medical microbiology consultation.

Medical microbiologists, defined as doctoral-level laboratory directors with subspecialty training in medical microbiology, lead the clinical laboratory operations through activities such as clinical consultations, oversight of diagnostic testing menu, institutional leadership, education, and scholastic activities. However, unlike their clinical colleagues, medical microbiologists are largely unable to bill for clinical consultations performed within the hospital and, therefore, unable to generate relative value units or a similar quantifiable metric. As hospital budgets tighten and justification of staffing becomes a necessity, this may present a challenge to the medical microbiologist attempting to prove their value to the organization. To aid in providing tangible data, the Personnel Standards and Workforce subcommittee of the American Society for Microbiology conducted a multi-center study across seven medical centers to document clinical consultations and their impact. Consults were generated equally from internal (laboratory-based) and external (hospital-based) parties, with the majority directly impacting patient management. Near universal acceptance of the medical microbiologist's recommendation highlights the worth derived from their expertise. External consults required more time commitment from the medical microbiologist than internal consults, although both presented ample opportunity for secondary value, including impact through stewardship, education, clinical guidance, and cost reduction. This study is a description of the content and impact of consultations that underscore the importance of the medical microbiologist as a key member of the healthcare team. IMPORTANCE: Medical microbiologists are invaluable to the clinical microbiology laboratory and the healthcare system as a whole. However, as medical microbiologists do not regularly generate relative value units, capturing and quantifying the value provided is challenging. As hospital budgets tighten, justification of staffing becomes a necessity. To aid in providing tangible data, the Personnel Standards and Workforce subcommittee of the American Society for Microbiology conducted a multi-center study across seven medical centers to document clinical consultations and their impact. To our knowledge, this is the first study to provide detailed evaluation of the consultative value provided by medical microbiologists.

Development and Diagnostic Potential of a Novel Bartonella henselae-Specific Immunoglobulin.

Bartonella henselae is a gram-negative rod-shaped bacterium and is the primary causative agent of Cat Scratch Disease (CSD). Although the prevalence of CSD is low in the human population, the possibility of developing multi-organ complications, especially in vulnerable individuals, remains a serious cause for concern. The immunofluorescent assay (IFA) is currently one of the most common laboratory tests for the detection of antibodies to B. henselae in serum, however, it has several disadvantages. The enzyme-linked immunosorbent assay (ELISA) technique offers a more quantitative, sensitive, and cost-effective alternative to conventional IFAs. Here, we report the purification of a novel bioidentical polyclonal antibody from discarded human serum for use as a standard in ELISAs against B. henselae. This novel method of antibody production overcomes the many limitations of animal-derived antibodies while also offering a more robust, reproducible, and scalable antibody production alternative for the diagnosis of CSD.

Central role of the ramAR locus in the multidrug resistance in ESBL-Enterobacterales.

The aim of this study was to evaluate the proportion of resistance to a temocillin, tigecycline, ciprofloxacin, and chloramphenicol phenotype called t2c2 that resulted from mutations within the ramAR locus among extended-spectrum ß-lactamases-Enterobacterales (ESBL-E) isolated in three intensive care units for 3 years in a French university hospital. Two parallel approaches were performed on all 443 ESBL-E included: (i) the minimal inhibitory concentrations of temocillin, tigecycline, ciprofloxacin, and chloramphenicol were determined and (ii) the genomes obtained from the Illumina sequencing platform were analyzed to determine multilocus sequence types, resistomes, and diversity of several tetR-associated genes including ramAR operon. Among the 443 ESBL-E strains included, isolates of Escherichia coli (n = 194), Klebsiella pneumoniae (n = 122), and Enterobacter cloacae complex (Ecc) (n = 127) were found. Thirty-one ESBL-E strains (7%), 16 K. pneumoniae (13.1%), and 15 Ecc (11.8%) presented the t2c2 phenotype in addition to their ESBL profile, whereas no E. coli presented these resistances. The t2c2 phenotype was invariably reversible by the addition of Phe-Arg-ß-naphthylamide, indicating a role of resistance-nodulation-division pumps in these observations. Mutations associated with the t2c2 phenotype were restricted to RamR, the ramAR intergenic region (IR), and AcrR. Mutations in RamR consisted of C- or N-terminal deletions and amino acid substitutions inside its DNA-binding domain or within key sites of protein-substrate interactions. The ramAR IR showed nucleotide substitutions involved in the RamR DNA-binding domain. This diversity of sequences suggested that RamR and the ramAR IR represent major genetic events for bacterial antimicrobial resistance.IMPORTANCEMorbimortality caused by infectious diseases is very high among patients hospitalized in intensive care units (ICUs). A part of these outcomes can be explained by antibiotic resistance, which delays the appropriate therapy. The transferable antibiotic resistance gene is a well-known mechanism to explain the high rate of multidrug resistance (MDR) bacteria in ICUs. This study describes the prevalence of chromosomal mutations, which led to additional antibiotic resistance among MDR bacteria. More than 12% of Klebsiella pneumoniae and Enterobacter cloacae complex strains presented mutations within the ramAR locus associated with a dysregulation of an efflux pump called AcrAB-TolC and a porin: OmpF. These dysregulations led to an increase in antibiotic output notably tigecycline, ciprofloxacin, and chloramphenicol associated with a decrease of input for beta-lactam, especially temocillin. Mutations within transcriptional regulators such as ramAR locus played a major role in antibiotic resistance dissemination and need to be further explored.

Inoculum Size and False-Positive Detection of NDM- and OXA-48-Type Carbapenemases Using Two Multiplex Lateral Flow Assays.

The NG-Test CARBA 5 and Carbapenem-resistant K.N.I.V.O. Detection K-Set are lateral flow assays (LFAs) that rapidly detect five carbapenemases (KPC, NDM, IMP, VIM and OXA-48-like). We evaluated the effect of inoculum size on the performance of these two assays using 27 Enterobacterales isolates. Whole-genome sequencing (WGS) was used as the reference method. Using the NG-Test CARBA 5, eight Serratia spp. and six M. morganii isolates showed false-positive NDM results with a high inoculum. Using the Carbapenem-resistant K.N.I.V.O. Detection K-Set, eight M. morganii, four Serratia spp. and one K. pneumoniae isolates showed false-positive NDM and/or OXA-48-like bands at large inoculum sizes, while the other two M. morganii isolates demonstrated false-positive NDM and OXA-48-like results at all inoculum sizes. The false-positive bands varied in intensity. WGS confirmed that no carbapenemase gene was present. No protein sequence with a ≥50% identity to NDM or OXA-48-like enzymes was found. This study emphasizes the importance of assessing inoculum size in the diagnostic evaluation of LFAs.

Longitudinal molecular analysis of clinical and fecal Escherichia coli isolates at a Veterans Affairs Medical Center in Minnesota, USA, 2012-2019.

Introduction: Extraintestinal Escherichia coli infections represent a growing public health threat, However, current studies often overlook important factors such as temporal patterns of infection, phylogenetic and clonal background, or the host gut E. coli population, despite their likely significance. Methods: In this study, we analyzed >7000 clinical E. coli isolates from patients at the Minneapolis Veterans Affairs Health Care System (2012-2019), and concurrent fecal E. coli from uninfected veterans. We assessed phylogenetic group distribution, membership in selected sequence types (STs), and subsets thereof-including the pandemic, resistance-associated ST131-H30R, and ST1193 lineages-and strain type, as defined by pulsed-field gel electrophoresis. We then analyzed these features alongside the temporal patterns of infection in individual hosts. Results: The H30R lineage emerged as the leading lineage, both overall and among fluoroquinolone-resistant isolates, with ST1193 following among fluoroquinolone-resistant isolates. Recurrences were common, occurring in 31% of subjects and 41% of episodes, and often multiple and delayed/prolonged (up to 23 episodes per subject; up to 2655d post-index). Remarkably, these recurrences typically involved the subject's index strain (63% of recurrences), even when affecting extra-urinary sites. ST131, H30R, ST1193, and fluoroquinolone-resistant strains generally caused significantly more recurrences than did other strains, despite similar recurrence intervals. ST131 strain types shifted significantly over the study period. Infection-causing strains were commonly detectable in host feces at times other than during an infection episode; the likelihood of detection varied with surveillance intensity and proximity to the infection. H30R and ST1193 were prominent causes of fecal-clinical clonal overlap. Discussion: These findings provide novel insights into the temporal and clonal characteristics of E. coli infections in veterans and support efforts to develop anti-colonization interventions.

Deep learning model to discriminate diverse infection types based on pairwise analysis of host gene expression.

Accurate detection of pathogens, particularly distinguishing between Gram-positive and Gram-negative bacteria, could improve disease treatment. Host gene expression can capture the immune system's response to infections caused by various pathogens. Here, we present a deep neural network model, bvnGPS2, which incorporates the attention mechanism based on a large-scale integrated host transcriptome dataset to precisely identify Gram-positive and Gram-negative bacterial infections as well as viral infections. We performed analysis of 4,949 blood samples across 40 cohorts from 10 countries using our previously designed omics data integration method, iPAGE, to select discriminant gene pairs and train the bvnGPS2. The performance of the model was evaluated on six independent cohorts comprising 374 samples. Overall, our deep neural network model shows robust capability to accurately identify specific infections, paving the way for precise medicine strategies in infection treatment and potentially also for identifying subtypes of other diseases.

Microbial diagnostics in periodontal diseases.

Microbial analytical methods have been instrumental in elucidating the complex microbial etiology of periodontal diseases, by shaping our understanding of subgingival community dynamics. Certain pathobionts can orchestrate the establishment of dysbiotic communities that can subvert the host immune system, triggering inflammation and tissue destruction. Yet, diagnosis and management of periodontal conditions still rely on clinical and radiographic examinations, overlooking the well-established microbial etiology. This review summarizes the chronological emergence of periodontal etiological models and the co-evolution with technological advances in microbial detection. We additionally review the microbial analytical approaches currently accessible to clinicians, highlighting their value in broadening the periodontal assessment. The epidemiological importance of obtaining culture-based antimicrobial susceptibility profiles of periodontal taxa for antibiotic resistance surveillance is also underscored, together with clinically relevant analytical approaches to guide antibiotherapy choices, when necessary. Furthermore, the importance of 16S-based community and shotgun metagenomic profiling is discussed in outlining dysbiotic microbial signatures. Because dysbiosis precedes periodontal damage, biomarker identification offers early diagnostic possibilities to forestall disease relapses during maintenance. Altogether, this review highlights the underutilized potential of clinical microbiology in periodontology, spotlighting the clinical areas most conductive to its diagnostic implementation for enhancing prevention, treatment predictability, and addressing global antibiotic resistance.