Detection and Analysis of Clinical Microbial Infections, Third Edition

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Medical Microbiology".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 873

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Laboratorio di Patologia delle Infezioni Associate all’Impianto (Research Unit on Implant Infections), IRCCS Rizzoli Orthopaedic Institute, Bologna, Italy
Interests: implant-associated infections; anti-infective substances and strategies; virulence factors; bacterial biofilm; bacterial molecular epidemiology
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Special Issue Information

Dear Colleagues,

This Special Issue is the third edition of our previous Special Issues, “Detection and Analysis of Clinical Microbial Infections” and “Detection and Analysis of Clinical Microbial Infections, Second Edition”.

Microbiological infections and diseases can be caused by bacteria, viruses, parasites, and fungi. This Special Issue has caused worldwide concern and requires the rapid detection and identification of the pathogens responsible for microbial infections. The first crucial and complex phase of the diagnostic process is the definition of the methods for collecting microbiological samples. In fact, depending on the heterogeneous diffusion and probable low number of pathogenic microorganisms, as well as on the chosen diagnostic method that will be used, sampling can be considered a difficult step, especially in chronic infections. The identification methods can be grouped into different clinical–diagnostic categories, namely, methods of isolation and culture with the determination of phenotypic and biochemical characteristics; morphological observation under microscope, particularly used for mixed microbial populations and non-culturable pathogens; antigenic tests, commonly used for their rapidity and simplicity; serological assays, with high specificity and sensitivity; and molecular biology techniques, for a definite microorganism recognition. "Omics" technologies, in particular genomics (PCR, PFGE, ribotyping, RFLP, RAPD-PCR, DNA sequencing, WGS) and transcriptomics (qPCR, RNA sequencing), but also proteomics (MALDI-TOF MS) and metabolomics (mass spectrometry-based methods), with an improved advancement of their limit of detection, are considered the cornerstones of clinical microbial analysis.

In addition to the demand for rapid and accurate diagnosis, due to new emerging microbial pathogens, there is a need for greater standardization of testing and centralized laboratories with the ability to collect and analyze large quantities of samples and perform various identification techniques.

Research articles and systematic reviews are both welcome.

Manuscript topics may cover the following topics:

  • Identification of unculturable pathogens and mixed microbial populations.
  • Sampling, culture, and isolation of the pathogen responsible for infectious diseases.
  • Advantages and limits of clinical microbial identification techniques.
  • New molecular biology techniques for microbial identification.
  • Standardization of techniques and sample data centralization.

Dr. Stefano Ravaioli
Guest Editor

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Microorganisms is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • microorganisms’ detection and analysis
  • clinical microbiology
  • identification technologies
  • new identification methods
  • heterogeneous dissemination
  • unculturable pathogens
  • mixed microbial populations
  • new emerging pathogens
  • genomics
  • transcriptomics
  • proteomics
  • metabolomics
  • standardization of testing
  • sample data centralization

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Published Papers (1 paper)

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Research

16 pages, 904 KB  
Article
Multidrug-Resistant Tuberculosis in Rural Eastern Cape, South Africa: Clinical, Bacteriological, and Programmatic Predictors of Poor Treatment Outcomes
by Mbulelo Cebisa, Ntandazo Dlatu, Mojisola Clara Hosu, Teke Apalata and Lindiwe Modest Faye
Microorganisms 2026, 14(3), 690; https://doi.org/10.3390/microorganisms14030690 - 18 Mar 2026
Viewed by 548
Abstract
Drug-resistant tuberculosis (DR-TB), particularly multidrug-resistant TB (MDR-TB), remains a significant public health challenge in rural South Africa, where diagnostic and treatment infrastructure is limited. This study aimed to assess resistance patterns, bacillary load, treatment outcomes, and predictors of MDR-TB in the O.R. Tambo [...] Read more.
Drug-resistant tuberculosis (DR-TB), particularly multidrug-resistant TB (MDR-TB), remains a significant public health challenge in rural South Africa, where diagnostic and treatment infrastructure is limited. This study aimed to assess resistance patterns, bacillary load, treatment outcomes, and predictors of MDR-TB in the O.R. Tambo District of the Eastern Cape Province. Although isoniazid monoresistant TB (Hr-TB) was identified, its analysis was descriptive due to the limited sample size. A retrospective cohort analysis was conducted on bacteriologically confirmed TB cases (n = 477) diagnosed between 2020 and 2022. The data collected included demographic and clinical variables, smear and culture results, resistance patterns, and treatment outcomes. Drug resistance was categorized as MDR-TB, Hr-TB, or fully susceptible. Outcomes were classified as favorable, unfavorable, lost to follow-up, or ongoing. Logistic regression identified predictors of MDR-TB. DR-TB prevalence was 11.3% (n = 54), with MDR-TB accounting for 10.7% (n = 51) and Hr-TB for 0.6% (n = 3). Prior TB treatment was significantly associated with MDR-TB (adjusted odds ratio [aOR] 4.45, 95% CI: 1.89–10.48). Smear positivity was associated with MDR-TB in univariate analysis (OR 5.0), although its effect diminished in multivariable analysis (aOR 0.40, 95% CI: 0.12–1.36), suggesting confounding by bacillary load. Culture positivity was a strong independent predictor (aOR 27.71, 95% CI: 8.84–86.85), indicating a higher mycobacterial burden among MDR-TB cases. MDR-TB patients had significantly poorer treatment outcomes, with a high rate of unfavorable outcomes and loss to follow-up. MDR-TB dominates the resistance landscape in this rural district, primarily driven by prior treatment and high bacillary loads. The study highlights the need for targeted interventions, including enhanced diagnostic capacity, improved clinical governance, and community-based support systems, to optimize the detection and management of MDR-TB. Full article
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