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Syracuse University

Monitoring Bacteria Cultures Using Near Infrared (nir) Binary Spectronephelometry (bsn), Raman Spectra and Principal Component Analysis (pca)

Abstract

dc:description.abstract

<p>Current noninvasive methods cannot continuously and simultaneously monitor the concentrations of cells and media components that define the state of native bacterial cultures, because of changing turbidity. A new technique, binary spectronephelometry (BSN) has the same or better sensitivity and precision for population monitoring as optical density at 600nm (OD600), while simultaneously measuring metabolic processes. The BSN algorithm uses laser induced emission to probe mildly turbid media i.e., propagation of light occurs in the single scattering regime. A BSN "training set" associates a grid of elastic emission measurements, comprising Rayleigh and Mie scattering, and inelastic emission measurements, comprising fluorescence and Raman emission, with a grid of varying known concentrations of bacteria and media. For the normal lifecycle culture and for some but not all growth media, the results confirmed the linear dependence of the two measured signals on the concentration of bacteria and medium dilutions, and agreement with OD600. Having thus confirmed basic assumptions and a calibrated algorithm, various bacteria cultures were monitored over time, producing quantitative "growth curves" for the bacteria and "depletion curves" for media. Simultaneously obtained Raman spectra demonstrate glucose uptake and conversion into bacterial membrane phospholipids. Beyond the normal life cycle, a few examples of using BSN to monitor cultures subjected to external perturbations are shown. Specific characteristics of Principal Component Analysis (PCA) of Raman spectra, and their variation in bacterial cultures, as well as assessing the role of bacterial transport e.g., diffusion in performing and analyzing BSN, are presented.</p>

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Chemistry
Year
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ortiz, Steven
Contributors dc:contributor
  • Chaiken, Joseph

Subjects

dc:subject × 11

Identifiers

dc:identifier.*
Repository record dc:identifier
https://surface.syr.edu/etd/1475
OAI identifier oai:identifier
oai:surface.syr.edu:etd-2476

Chain of custody

source
Harvested from
Syracuse University
Base URL
surface.syr.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Ortiz, Steven. Monitoring Bacteria Cultures Using Near Infrared (nir) Binary Spectronephelometry (bsn), Raman Spectra and Principal Component Analysis (pca). Dissertation thesis, 2022. https://surface.syr.edu/etd/1475