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Al Hafi, L.; Alocilja, E.C. Morphometric Characterization of Bacteria Associated with Bacteremia. Encyclopedia. Available online: https://encyclopedia.pub/entry/58851 (accessed on 05 December 2025).
Al Hafi L, Alocilja EC. Morphometric Characterization of Bacteria Associated with Bacteremia. Encyclopedia. Available at: https://encyclopedia.pub/entry/58851. Accessed December 05, 2025.
Al Hafi, Ladees, Evangelyn C. Alocilja. "Morphometric Characterization of Bacteria Associated with Bacteremia" Encyclopedia, https://encyclopedia.pub/entry/58851 (accessed December 05, 2025).
Al Hafi, L., & Alocilja, E.C. (2025, August 28). Morphometric Characterization of Bacteria Associated with Bacteremia. In Encyclopedia. https://encyclopedia.pub/entry/58851
Al Hafi, Ladees and Evangelyn C. Alocilja. "Morphometric Characterization of Bacteria Associated with Bacteremia." Encyclopedia. Web. 28 August, 2025.
Peer Reviewed
Morphometric Characterization of Bacteria Associated with Bacteremia
This is a peer-reviewed entry published in Encyclopedia Journal, full entry can be found at 10.3390/encyclopedia5030130

Among the leading causes of bacteremia are Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus. E. coli and K. pneumoniae are increasingly exhibiting resistance to last-resort antibiotics, such as carbapenems. Rapid and accurate identification of these pathogens is critical for timely treatment and infection control. This paper aimed to develop a computer-aided bacterial morphometric technique for identifying and classifying wild-type E. coli, K. pneumoniae, and S. aureus in a field guide fashion. A 3D laser scanning confocal microscope was used to gather key parameters of each organism: length (L, µm), circular diameter (CD, µm), volume (V, µm3), surface area-to-cross-sectional area ratio (SA/CSA, unitless), surface uniformity ratio (Str), and surface texture ratio (Sdr). Microscope images and measurement results showed that S. aureus was spherical with the shortest length (1.08 µm) and smallest volume (0.52 µm3). E. coli and K. pneumoniae were rod-shaped with lengths >2.0 µm and volumes >1.0 µm3. Carbapenem-resistant (CR) strains exhibited larger volumes than their wild-type counterparts. Surface parameters further differentiated strains: wild-type E. coli had a greater surface texture or a less smooth surface (larger Sdr) than K. pneumoniae (lower Sdr) did. CR E. coli had more surface uniformity (lower Str) than CR K. pneumoniae did. A dichotomous key based on shape, circular diameter, volume, length, and surface characteristics was developed to classify the species using a series of paired, contrasting features. This morphometric analysis can aid researchers in quickly identifying bacteria, leading to faster diagnosis of life-threatening diseases and improved treatment decisions.

bacteremia antimicrobial resistance (AMR) diagnostics dichotomous morphometrics size surface roughness E. coli K. pneumoniae S. aureus
Bacteremia is the presence of viable bacteria in circulating blood, and it is associated with significant morbidity and mortality [1]. Various factors, including microbial infection, medical procedures, or the use of medical devices, can cause bacteremia [1]. In a surveillance study between 2002 and 2020, Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus were the top three causes of bacteremia in Taiwan [2]. Sepsis can develop from bacteremia if the body’s immune system is unable to control the infection [2]. It can rapidly progress to organ failure and can lead to shock and death if not treated quickly [2]. Rapid and accurate identification of the causative bacteria is crucial for effective treatment. Current methods of identification include culture (colony morphology and biochemical tests), staining (Gram-positive and Gram-negative stains), genomics (polymerase chain reaction, microarrays, and ribotyping), and other advanced techniques (mass spectrometry and flow cytometry). However, these techniques are time-consuming and expensive. Bacterial identification based on morphology is gaining popularity [3]. It is rapid, reduces costs, and yields intuitive results [3][4]. Modern morphometry utilizes advanced computer-assisted image analysis software to interface an image with geometric software that measures specific biological features [4]. It is a quantitative analysis of the size and shape of geometric features of cells, cell organelles, and/or biomarkers [4]. Bacterial morphometry allows for a systematic approach to bacterial identification, progressing from easily observable characteristics to more detailed microscopic and biochemical analyses. It functions like a field guide by providing a framework for identifying bacteria based on their characteristic shapes, arrangements, and visible growth patterns.
The emergence of bacteria with antimicrobial resistance (AMR) has further exacerbated the poor outcomes associated with bacteremia [2]. The rise in AMR makes diagnosis and treatment increasingly complex [5][6]. AMR is one of the top three major public health threats by the World Health Organization (WHO) and is the third leading cause of death after cardiovascular diseases [6]. An estimated 1.27 million deaths were attributed to antimicrobial-resistant infections in 2019 alone, while nearly 5 million deaths were somehow associated with drug-resistant infections [6]. AMR infections can lead to severe complications, especially among immunocompromised patients [7][8]. Therapeutic options for infections caused by antimicrobial-resistant bacteria are limited, resulting in prolonged illness and significant morbidity and mortality, with a high financial impact [8]. Many medical advances, such as organ transplants and cancer therapy, depend on the ability to fight infections with antimicrobials. If the ability to effectively treat those infections is lost, the ability to safely offer people many of the lifesaving and life-improving modern medical advances will be lost with it.
Beta-lactams, including penicillin, cephalosporin, monobactam, and carbapenem, are the most widely used antibiotics worldwide, and they are reserved only for human use [9]. Carbapenems are the most effective antimicrobial agents against both Gram-positive and Gram-negative bacteria, exhibiting a broad spectrum of antibacterial activity. Thus, the rise in carbapenem-resistant (CR) bacteria is concerning, as it limits treatment options and is associated with increased morbidity, mortality, and healthcare costs [6][10]. CR can induce structural and physiological changes in bacterial cells, potentially altering their morphology and growth patterns [11][12][13].
Thus, this paper aimed to develop a computer-aided bacterial morphometric technique for identifying and classifying wild-type Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus in a field guide fashion [13]. The first classification employed shape, followed by other parameters. Bacteria have distinct shapes, such as (1) spherical or round (cocci), in clusters (e.g., Staphylococcus), in chains (e.g., Streptococcus), in pairs with pointed ends (e.g., Streptococcus pneumoniae;), and in pairs with kidney bean shape (e.g., Neisseria); (2) rods (bacilli), with square ends (e.g., Bacillus), with rounded ends (e.g., Salmonella), club-shaped (e.g., Corynebacterium), fusiform (e.g., Fusobacterium), and comma-shaped (e.g., Vibrio); and (3) spiral (Spirochetes), relaxed coil (e.g., Borrelia), and tightly coiled (e.g., Treponema) [11].
The morphometric technique was extended to classify CR E. coli and CR K. pneumoniae since both pathogens are frequently known to develop CR, but not on S. aureus, because it is not commonly known to have resistance to carbapenem. By mapping morphometric traits to specific species, this guide supports faster, image-based identification and strengthens the ability to respond to the growing threats of AMR.

References

  1. McNamara, J.F.; Righi, E.; Wright, H.; Hartel, G.F.; Harris, P.N.A.; Paterson, D.L. Long-term morbidity and mortality following bloodstream infection: A systematic literature review. J. Infect. 2018, 77, 1–8.
  2. Huang, Y.-C.; Kuo, S.-C.; Fang, C.-T.; Lauderdale, T.-L. Changing epidemiology and antimicrobial resistance of bacteria causing bacteremia in Taiwan: 2002–2020. Microbiol. Spectr. 2024, 12, e00608–e00624.
  3. Al Hafi, L.; Franco, A.J.; Kao, K.; Alocilja, E.C. Field Guide: Morphometric Visualization and Characterization of Selected Foodborne Pathogens Using Advanced Imaging Techniques. Encyclopedia 2025, 5, 47.
  4. Wang, X.; Shi, Y.; Guo, S.; Qu, X.; Xie, F.; Duan, Z.; Hu, Y.; Fu, H.; Shi, X.; Quan, T.; et al. A Clinical Bacterial Dataset for Deep Learning in Microbiological Rapid On-Site Evaluation. Sci. Data 2024, 11, 608.
  5. Abban, M.K.; Ayerakwa, E.A.; Mosi, L.; Isawumi, A. The burden of hospital acquired infections and antimicrobial resistance. Heliyon 2023, 9, e20561.
  6. Salam, M.A.; Salam, A.; Al-Amin, Y.; Pawar, J.S.; Akhter, N.; Rabaan, A.A.; Alqumber, M.A.A. Antimicrobial Resistance: A Growing Serious Threat for Global Public Health. Healthcare 2023, 11, 1946.
  7. Abbara, S.; Guillemot, D.; Smith, D.R.; El Oualydy, S.; Kos, M.; Poret, C.; Breant, S.; Brun-Buisson, C.; Watier, L. Antimicrobial Resistance as Risk Factor for Recurrent Bacteremia after Staphylococcus aureus, Escherichia coli, or Klebsiella spp. Community-Onset Bacteremia. Emerg. Infect. Dis. 2024, 30, 974–983.
  8. Elbehiry, A.; Marzouk, E.; Aldubaib, M.; Moussa, I.; Abalkhail, A.; Ibrahem, M.; Hamada, M.; Sindi, W.; Alzaben, F.; Almuzaini, A.M.; et al. Pseudomonas species prevalence, protein analysis, and antibiotic resistance: An evolving public health challenge. AMB Express 2022, 12, 53.
  9. Meletis, G. Carbapenem resistance: Overview of the problem and future perspectives. Ther. Adv. Infect. Dis. 2016, 3, 15–21.
  10. Ahmed, S.K.; Hussein, S.; Qurbani, K.; Ibrahim, R.H.; Fareeq, A.; Mahmood, K.A.; Mohamed, M.G. Antimicrobial resistance: Impacts, challenges, and future prospects. J. Med. Surg. Public Health 2024, 2, 100081.
  11. Levinson, W.; Chin-Hong, P.; Joyce, E.A.; Nussbaum, J.; Schwartz, B. Structure of Bacterial Cells. In Review of Medical Microbiology & Immunology: A Guide to Clinical Infectious Diseases, 16th ed.; McGraw Hill: New York, NY, USA, 2020; Available online: https://accessmedicine.mhmedical.com/content.aspx?bookid=3123&sectionid=261995947 (accessed on 30 June 2025).
  12. Amako, K.; Meno, Y.; Takade, A. Fine structures of the capsules of Klebsiella pneumoniae and Escherichia coli K1. J. Bacteriol. 1988, 170, 4960–4962.
  13. Ikebe, M.; Aoki, K.; Hayashi-Nishino, M.; Furusawa, C.; Nishino, K. Bioinformatic analysis reveals the association between bacterial morphology and antibiotic resistance using light microscopy with deep learning. Front. Microbiol. 2024, 15, 1450804.
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Subjects: Microbiology
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : Ladees Al Hafi , Evangelyn C. Alocilja
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Online Date: 28 Aug 2025
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