Title:Beyond Numbers: The Informative Patterns of Immuno-Staphylococcal Dynamics
Volume: 21
Issue: 16
Author(s): Ariel L. Rivas, Almira L. Hoogesteijn and Renata Piccinini
Affiliation:
Keywords:
Infection, MRSA, MSSA, complexity, systems, dynamics, three-dimensional, cutoff-free discrimination.
Abstract: To evaluate new drugs, the immune system should be considered. Here we evaluated a proof-of-concept
that uncovers bacterial-leukocyte interactions. Analyzing longitudinal leukocyte data from bovines infected with
either methicillin-resistant (MRSA) or methicillin-susceptible (MSSA) Staphylococcus aureus, two methods were
investigated: (i) an approach that assesses lymphocytes, monocytes, or neutrophils, separately, and (ii) a method
that, using dimensionless indicators (products, ratios, or combinations derived from leukocyte data), explores the
dynamics of leukocyte relationships in three-dimensional (3D) space and identifies data subsets of informative
value.
The classic approach not always distinguished infected from non-infected cows. In contrast, the alternative approach differentiated noninfected
from infected animals and distinguished early MRSA from early MSSA and late MRSA infections.
Discrimination was associated with the use of dimensionless indicators. When measured in 3D space, such indicators generated a very
large number of combinations, which helped detect data subsets usually unobserved, such as non-overlapping infection-negative and
-positive subsets, and several disease stages. The validity of such data subsets was determined with biologically interpretable data.
This graphic, pattern recognition-based information system included but did not depend on any one number or variable. Because it can
detect functions (relationships that involve two or more elements), in real time, if shown reproducible, the analysis of complex hostmicrobial
dynamics could be used to evaluate antimicrobials.
