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
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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, µm
3), 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 µm
3).
E. coli and
K. pneumoniae were rod-shaped with lengths >2.0 µm and volumes >1.0 µm
3. 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.
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