What Wavelengths Might You Choose to Measure Onp
Biomed Opt Express. 2016 Oct 1; 7(10): 4034–4042.
Wavelength-normalized spectroscopic analysis of Staphylococcus aureus and Pseudomonas aeruginosa growth rates
Samantha Eastward. McBirney
aneDepartment of Biomedical Engineering science, Academy of Southern California, 3651 Watt Way, Los Angeles, CA 90089, USA
Kristy Trinh
2School of Chemist's, University of Southern California, 1985 Zonal Artery, CA 90089, USA
Annie Wong-Beringer
2School of Chemist's, University of Southern California, 1985 Zonal Avenue, CA 90089, USA
Andrea M. Armani
1Department of Biomedical Engineering, Academy of Southern California, 3651 Watt Way, Los Angeles, CA 90089, Usa
3Mork Family Department of Chemical Engineering and Materials Scientific discipline, University of Southern California, 3651 Watt Way, Los Angeles, CA 90089, The states
Received 2016 Jul thirteen; Revised 2016 Sep one; Accepted 2016 Sep ix.
Abstract
Optical density (OD) measurements are the standard approach used in microbiology for characterizing leaner concentrations in culture media. OD is based on measuring the optical absorbance of a sample at a single wavelength, and whatsoever error will propagate through all calculations, leading to reproducibility bug. Here, we use the conventional OD technique to measure the growth rates of ii different species of bacteria, Pseudomonas aeruginosa and Staphylococcus aureus. The aforementioned samples are also analyzed over the unabridged UV-Vis wavelength spectrum, assuasive a distinctly different strategy for data analysis to be performed. Specifically, instead of but analyzing a single wavelength, a multi-wavelength normalization process is implemented. When the OD method is used, the detected signal does not follow the log growth curve. In contrast, the multi-wavelength normalization process minimizes the impact of bacteria byproducts and environmental racket on the bespeak, thereby accurately quantifying growth rates with high fidelity at depression concentrations.
OCIS codes: (300.6550) Spectroscopy, visible; (120.1880) Detection; (170.1530) Cell analysis
one. Introduction
Understanding and accurately characterizing the dissimilar stages of microbial growth plays a key role in a wide range of fields spanning from therapeutic design and development to diagnostics and disease prevention. Microbial growth is characterized by four singled-out phases: lag phase, exponential or log phase, stationary phase, and decease phase. The lag phase is considered to be the initial period of slow growth, during which fourth dimension cells are enlarging and synthesizing critical proteins and metabolites. This stage is followed by the exponential growth phase, sometimes known as the logarithmic growth phase. During growth, prison cell partitioning proceeds at a constant rate with the number of cells doubling every unit of time, known as the doubling, or generation, time. Generation times for leaner vary widely and can range from minutes to days. During the stationary phase, conditions brainstorm to get unfavorable for growth, and bacteria stop replicating. During the decease phase, cells lose viability [1–3]. In order to fully map out this process, a measurement method must be able to take readings speedily, iteratively, and reliably over long periods of fourth dimension. Additionally, the technique should exist resistant to potentially confounding signals, such as waste byproducts from the cells and thermal drifts.
Every bit a consequence of its importance, a broad range of methods accept been developed for determining the growth charge per unit, ranging from ultrasensitive menstruation cytometry to automated counting of bacteria colonies in images. When accuracy is disquisitional, flow cytometry is typically the preferred solution. Yet, information technology requires the bacteria to be fluorescently labeled, either through genetic engineering (due east.g. GFP, RFP) or with a fluorescent tag [4,5]. In contrast, bacteria colony counting does non have this requirement, just it is significantly less sensitive and is prone to large fault values [6]. The importance of these measurements in a wide range of settings from biomanufacturing to basic research has motivated other label-costless methods based on spectroscopy to exist developed.
The ascension in advanced spectroscopy methods has provided a broad toolset for biologists to choose from when performing these belittling measurements. For example, using Raman and FTIR spectroscopy, researchers have monitored the formation of individual bacterium and bacteria layers and the layer response to different antibiotics, enabling rapid optimization of therapeutics [7–11]. However, research has also shown that the results can exist strongly dependent on the instrument configuration [12–14]. Additionally, the methods are extremely time-consuming and rely on access to avant-garde instrumentation. Given the important role that these results play throughout microbiology, a quantitative, reproducible, and rapid technique for determining leaner concentration in prison cell media tin can significantly impact and improve a wide range of applications [15].
In industrial and microbiology lab settings, optical density (OD) measurements take become the preferred approach because of their simplicity and rapid time to answer. Based on optical spectroscopy, an OD measurement characterizes the amount of light that is lost due to scattering and absorption at a single wavelength [16]. In bacteria analysis, 600 nm is frequently used, resulting in the classification OD600. Based on previous work, information technology is presumed that the OD correlates directly with the cell concentration [17]. Several studies came to the conclusion that OD600 measurements are very reliable and reproducible [xviii]; however, this decision was based on accepting error rates greater 50%. This error tin be attributed to many issues that are readily solvable.
For instance, it is known that bacteria generate byproducts as they grow. These byproducts can lead to an increase in absorption. Therefore, in improver to the optical loss due to handful, these byproducts may also contribute to the betoken. Additionally, the internal, sub-wavelength components of the bacteria could likewise contribute to an increment in optical loss. Finally, bacteria are found in a range of morphologies and sizes. Because OD600 measurements are based on the supposition that the handful betoken directly correlates with the concentration, this variation could undermine this relationship. Notably, some bacteria are actually smaller than 600 nm, making them poor-scatterers [19]. Yet, other bacteria will dodder or form long bondage during growth [twenty] when a critical concentration is reached, resulting in a non-compatible growth signal. Given the variety in size, shape, and growth patterns of various bacteria, it would seem advantageous to use a multi-wavelength analysis arroyo to maximize the accuracy of the betoken.
While the OD600 technique is attractive for its simplicity, relying on a single wavelength can significantly increase the affect of these morphological and ecology variations on the detected signal. Therefore, taking into business relationship recent advances in the field of optical spectroscopy and signal assay, it is critical to rigorously evaluate the efficacy and accuracy of the current OD600 approach, especially given previous work demonstrating discrepancies between different spectrophotometers [15]. By conducting total spectrophotometric analyses on samples every bit opposed to only looking at a single wavelength of calorie-free, perchance it is possible to glean more information on the growth patterns of samples, thereby shedding more lite on the different growth stages.
To study this hypothesis, nosotros chose to measure the growth kinetics of Pseudomonas aeruginosa and Staphylococcus aureus. These two bacteria strains were chosen for the nowadays written report for both their similarities and their differences. Their similarities lie in the manner of infection and virulence, while their differences lie in more fundamental aspects; namely, their shape, motility, and growth patterns. P. aeruginosa is ane of the leading nosocomial pathogens, responsible for 10-15% of nosocomial infections worldwide, and it has joined the rank of "superbugs" due to its resistance to practically all antimicrobial drugs available on the market [21–23]. Additionally, this bacterium is very adjustable, and it is able to continuously develop new resistance mechanisms every bit new antimicrobial agents are created [21,24,25]. Similarly, S. aureus is a unsafe and versatile pathogen that causes a variety of severe diseases; near frequently, skin and respiratory tract infections [26]. S. aureus is the well-nigh mutual nosocomial pathogen, and information technology is associated with high morbidity and mortality, causing clinical disease in 2% of all patient admissions [27,28]. Similar P. aeruginosa, S. aureus is besides an extraordinarily adjustable pathogen with a proven ability to develop resistance.
While P. aeruginosa and S. aureus exhibit many similarities, in that location are as well several key differences between these two leaner (Fig. i(a)-ane(b)). P. aeruginosa is a Gram-negative rod-shaped bacterium, known for growing in isolation from other colonies. Almost all strains are motile past means of a single polar flagellum [29]. South. aureus is a Gram-positive, non-motile, minor, circular-shaped bacteria, typically found growing in grape-like clusters [30]. Characterizing the growth cycles of P. aeruginosa and Southward. aureus will lead to a ameliorate agreement of the pathogenesis of infections acquired by these leaner. Additionally, these two leaner provide a rigorous and biologically relevant test of our arrangement, allowing us to verify the universal applicability of the method.
a) Rendering of S. aureus, b) Rendering of P. aeruginosa, c) Optical image of 4 dissimilar clinical South. aureus strains grown on claret agar plate.
2. Materials and methods
2.1 Preparation of bacterial cultures
Iv different clinical strains of S. aureus (LAC91, KH38, HH49, and HH36) and one laboratory reference strain of P. aeruginosa (PA01) were reconstituted from frozen stock. Clinical strains were obtained directly from patient specimens, whereas laboratory reference strains have been sub-cultured for decades since their first isolation. P. aeruginosa (PA01) comes from a strain originally isolated in 1955, and subcultures have been passaged on laboratory media and shared among microbiological laboratories all over the world since. It is important to annotation that, in the course of sequential in vitro passage, laboratory reference strains may take significantly differentiated depending on growth conditions from non-passaged clinical samples. After lightly scratching the surface of the frozen stock with a sterile inoculating loop, bacterial cultures were suspended in 5 mL tryptic soy broth (TSB) using a vortex mixer and grown in a shaking incubator at 37°C for 24 hours. The civilization was kept in a shaking incubator for the duration of the experiments.
two.ii Training of bacterial culture dilutions
At the start of the measurements, the cultures were diluted. Two different dilutions were used in the present series of measurements.
To perform the colony counting, the cultures were plated at a 10−10 dilution, diluted in tryptic soy goop. This dilution factor was chosen for the purpose of ensuring a representative number of colonies. If at that place are too many colonies nowadays when plating, counting them is not possible and the numbers are too loftier to exist relevant, while if there are besides few colonies, in that location are not enough for the count to be significant. Additionally, in guild for colonies to form visibly, in that location must be a minimum number of leaner.
For the OD600 and the multi-wavelength normalization measurements, the level of dilution was 1:40. This dilution was performed in fifteen-minute intervals, in fourth dimension with the spectroscopic measurements. At each interval, 50 µL from the overnight culture was added to 1950 µL of fresh sterile tryptic soy broth, resulting in a one:40 dilution. This concentration was optimized to match the working range of the spectrophotometers used for these measurements (Biochrom WPA Spectrawave S1200 Spectrophotometer and Tecan Magellan Sunrise Spectrophotometer).
2.3 Colony counting
As an alternative to the OD600, colony-counting measurements were also performed. Five hours into the spectroscopy measurements, the bacteria strains were plated to yield an guess concentration. S. aureus strains were plated on blood agar plates. 10 µL was drawn from each 10−10 dilution and dropped onto the plate. Using a sterile loop, the bacteria were spread over a department of the plate to create a streak in one quadrant. This procedure was repeated with a fresh sterile loop for each of the subsequent Southward. aureus strains, filling up each of the iv quadrants of the claret agar plate. A similar procedure was used to plate the P. aeruginosa strain; however, a Pseudomonas Isolation Agar (PIA) plate was used. Plates were incubated overnight at 37°C and colonies counted 24 hours later on.
Figure 1(c) shows the optical images of the Due south. aureus bacteria cultures plated at x−x dilutions. The bacterial concentration for each strain is calculated in colony-forming units per milliliter, the standard method used for obtaining microbial concentrations. To determine this value, the number of colonies present is counted. The number of colonies is so multiplied past the dilution cistron and divided by the volume plated, in milliliters. Given that the dilution gene is 10−10 and strains were plated at 10 µL (or 10−2 mL), we can calculate the concentration in colony-forming units per milliliter past multiplying the number of colonies by 1012. Colony counts for each strain, as shown in Fig. one(c), were as follows: 113 colonies for KH38, 15 colonies for LAC91, 21 colonies for HH36, and 35 colonies for HH49. Therefore, based on the prototype and subsequent colony counts, the bacterial concentration is approximately determined to exist on the order of tenxiii - x14 colony-forming units per milliliter for each leaner strain. Yet, as can be seen, the size of the different colonies greatly varies, and several of the colonies appear to be merging. Both of these can result in a large error in this value.
2.iv OD600 measurements
OD600 measurements were performed using a Tecan Magellan Sunrise Spectrophotometer. This specific musical instrument is the standard i used for this measurement in a core facility. All measurements were conducted at room temperature and taken at 15-infinitesimal intervals for 11 hours, starting 24 hours later inoculation. At each interval, three separate 150 µL samples were measured, per 1:40 dilution of each strain, yielding three values that were and so averaged to obtain a more representative OD600 measurement. No subsequent data analysis was conducted on these measurements, per the protocol.
two.5 Multi-wavelength differential absorbance spectroscopy
The UV-Vis transmission spectra from the bacterial suspensions were recorded using a Biochrom WPA Spectrawave S1200 Spectrophotometer. We characterized the leaner over a wavelength range of 350 nm through 800 nm. At wavelengths as short as 250 nm, we would await to run into impairment to the cell [31]. Therefore, we did not go shorter than 350 nm, so as to avoid cellular impairment. At the commencement of each measurement interval, a groundwork or normalization spectrum was taken using a sample that only contained the TSB. All spectra were normalized using this spectrum by subtracting the absorbance of the growth media from the absorbance of the cultures for each bacteria strain at each time signal.
All measurements were conducted at room temperature and taken at 15-minute intervals for xi hours, starting 24 hours after inoculation, yielding xl-v data points for each strain. The resulting optical spectra were analyzed ii ways: 1) the absorbance at 600 nm was determined, and 2) a multi-wavelength normalization analysis was performed. The absorbance at 600 nm is determined from the UV-Vis absorbance spectra. These values can be directly compared with those from the OD600 system. The multi-wavelength normalization analysis is more complex.
Offset, every spectrum is converted into a iii-point wavelength-averaged spectra. The motivation for this averaging process is related to the wavelength accuracy (+/− 2 nm) and reproducibility (+/− ane nm) of the UV-Vis organization. These values are related to the accuracy and reproducibility of the scanning or moving grating. Considering the terminal goal is a differential measurement, in which sequential measurements are subtracted from each other, the accuracy and reproducibility of the wavelength plays a meaning role. The averaging procedure is very straightforward. If the output of the spectrophotometer at iii consecutive wavelengths (λ1, λ2, λthree) has the values A1, Atwo, A3, then the three-point averaged value is (A1 + A2 + A3)/iii at λ2. This process occurs for every set of three wavelengths, iteratively.
From the iii-point averaged spectra, 2 wavelengths and the associated absorbances are identified: ane) a wavelength that experiences a minimum modify in absorbance over time (λΔmin), and ii) a wavelength that experiences a maximum change in absorbance over time (λΔmax). The wavelength that undergoes the maximum alter and the minimum change for each bacterium was identified by calculating the total change in absorbance over time (αfinal – αo), with αfinal being the final absorbance at time t = eleven hours and αo being the initial absorbance at time t = 0 hours. The wavelengths that yield the greatest and the least differences in absorbance over fourth dimension were chosen for subsequent assay. In the terminal pace, the normalized absorbance is calculated by dividing the two absorbance values ((Δαmax)/ (Δαmin)).
3. Results and discussion
Figure ii(a) shows a subset of the forty-five UV-Vis spectra for the S. aureus strain HH49 after converting to the iii-point wavelength-averaged spectra. As tin can exist observed, some wavelengths experience a greater time-dependent modify than other wavelengths.
a) UV-Vis spectra for Southward. aureus strain HH49. Arrows indicate wavelengths chosen for subsequent assay. b) UV-Vis measurements at wavelengths of interest plotted at select intervals over fourth dimension. c) OD600 measurements plotted at select intervals over time. Error bars are shown for b) and c); however, the fault is and so small that the error bars are smaller than the symbols.
To more clearly see this behavior, the absorbance values at the six wavelengths indicated by black arrows in Fig. 2(a) are plotted in Fig. 2(b). These specific wavelengths were selected to either have minimum or maximum fourth dimension-dependent change. Several key points can exist made based on these results. First, the alter in absorbance at 600 nm actually falls in between these two extremes and, therefore, is not platonic for detection of bacteria growth. Additionally, all of the wavelengths with a large change are below 600 nm. When one considers the size of S. aureus, the reason for this dependence becomes axiomatic. S. aureus is approximately 600 nm in bore [32].
It is of import to verify that amend instrumentation is non responsible for the improved bespeak at the different wavelengths. To report this parameter, the reading at 600 nm from the UV-Vis is compared to the OD600 measurements. Figure two(c) plots the 600 nm absorbance values from the spectrophotometer and the OD600 measurements together to prove the comparison. The general trends are almost identical, every bit is the total signal change, though there is a constant offset. This constant offset could ascend from several unlike parameters including a wavelength calibration error – for example, if ane of the systems was not precisely measuring 600 nm. Still, given that it is a constant starting time, the results between the two systems are in practiced agreement.
Using measurements similar to the ones shown in Fig. 2(a), seven wavelengths were selected for each bacterium based on the same criteria (Fig. 3). For all four of the S. aureus strains, the wavelength that undergoes the maximum change is 446 nm, and the wavelength that undergoes the minimum modify is 787 nm. Notably, for P. aeruginosa, 644 nm changes the about while 600 nm changes the least, nevertheless information technology is the wavelength used in the typical OD600 measurements. These results were reproduced several times (N = 3), and the ideal wavelengths associated with each bacterium remained abiding.
Change in absorbance over time for seven wavelengths, including 600 nm, exhibiting significant or little change. The specific leaner plotted are: a) Southward. aureus, HH36 strain, b) South. aureus, HH49 strain, c) South. aureus, KH38 strain, d) S. aureus, LAC91 strain, and e) P. aeruginosa, PA01 strain. Error bars are shown on each plot; nevertheless, the mistake is so small that the error confined are smaller than the symbols.
Figure 4 shows the normalized differential absorbance (left centrality) and the OD600 measurement (correct axis) for each bacterium every bit a function of time. Several important points become immediately apparent upon analyzing the results. Showtime, while both the wavelength-normalized data and the OD600 data show a general increase in absorbance with fourth dimension, for the S. aureus, the functional form of this increase is completely different (Fig. 4(a)-iv(d)). Specifically, for all four strains, the wavelength-normalized data exhibits a well-defined log growth. In contrast, the OD600 shows a somewhat linear and somewhat log tendency over the time period studied. Information technology has been well established by dissimilar methods that the expected growth curve is logarithmic over this time period [33]. 2nd, for the example of P. aeruginosa, given the noise in the data, the OD600 is unable to find growth reliably considering the noise in the information is larger than the indicate, whereas the wavelength-normalized approach easily detects the growth curve with high fidelity (Fig. iv(east)). Therefore, for P. aeruginosa, this analysis method is truly an enabling approach.
Wavelength-normalized absorbance and OD600 for each strain plotted as a role of time. The specific bacteria plotted are: a) S. aureus, HH36 strain, b) Due south. aureus, HH49 strain, c) South. aureus, KH38 strain, d) S. aureus, LAC91 strain, and e) P. aeruginosa, PA01 strain. Fault confined are shown on each plot for both wavelength-normalized absorbance and OD600 measurements; however, the error is so modest for the wavelength-normalized absorbance that nigh of the error bars are smaller than the symbols, while the error is clearly visible for OD600 measurements.
Using the results shown in Fig. 4, the doubling fourth dimension for each bacteria strain is calculated. Discarding the lag and stationary phases of growth, we fit the linear portion of the exponential growth curve to a line. The slope of this line is known every bit µ. Dividing µ into ln(2) yields the doubling fourth dimension. Doubling times were as follows: 22.42 ± 2.1 minutes for LAC91, 33.44 ± 3.0 minutes for KH38, 37.98 ± five.4 minutes for HH49, 24.92 ± ane.8 minutes for HH36, and 157.17 ± nineteen.iv minutes for PA01. S. aureus has previously reported doubling times of between 24 and 57 minutes [32–34], while P. aeruginosa has reported doubling times of between 100 and 200 minutes [35,36]. Therefore, there is first-class agreement between the electric current results and previous results in the field. In contrast, the OD600 information taken in parallel is unable to be fit to an exponential function. As a result, it is not possible to calculate doubling times from the OD600 measurements for comparison.
iv. Conclusions
The present piece of work proposes and demonstrates that, by implementing a wavelength-normalization stride in the data analysis, the accuracy of characterizing the growth rate of a bacteria culture volition exist significantly improved over the conventional OD600 technique. The proposed method is verified using two distinctly dissimilar types of bacteria, P. aeruginosa and S. aureus, and the results obtained are in good agreement with previous values. In dissimilarity, due to poor absorbance at 600 nm, the classic OD600 measurement method is unable to detect the growth rate reliably. Our wavelength-normalization protocol to detect bacteria growth rates tin exist readily and easily adopted by enquiry labs, given that it simply requires the use of a standard spectrophotometer and implementation of a straightforward information analysis method. Measuring and monitoring bacteria growth rates plays a critical role in a wide range of settings, spanning from therapeutic design and evolution to diagnostics and disease prevention. Having a full agreement of the growth cycles of leaner known to cause severe infections and diseases volition pb to a improve understanding of the pathogenesis of these illnesses, leading to amend treatment and, ultimately, the development of a cure.
Funding
This piece of work was supported past the Part of Naval Research [N000141410374;, N000141110910]. S.E. McBirney was supported past an Alfred Mann Institute Graduate Enquiry Fellowship.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5102515/
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