To what extent do the phs 2.00, 3.00, 4.00, 5.00, 6.00, and 7.00 affect the growth of lactobacillus found in soy yogurt, measured at 625nm by a spectrophotometer?

The gut microbiota is defined as those microorganisms that live in vertebrates’ gastrointes6nal tracts. In humans, the gut represents the main site of survival of the human microbiota composed of several microbial strains (Dahiya & Nigam, 2022). This part of the body is highly addressed because it inhibits the coloniza6on of harmful bacteria, for6fies the layer of the internal mucosa, and strengthens the overall immune system (Xinzhou, Peng, & Xin, 2021) if a healthy balance between host bacteria and gut microorganisms is kept. Recent research has confirmed that the gut microbiome can be improved by the intake of func6onal foods, products with an ac6ve live popula6on of probio6cs, like dairy products(Dahiya & Nigam, 2022) containing lac6c acid bacteria, such as Lactobacillus (Na6onal Center for Complementary and Integra6ve Health, 2019).

Bacterial survival is closely 6ed to pH levels. These microorganisms thrive best within a specific, op6mal pH range. Any devia6on from this range can result in less effec6ve growth or even the death of the bacteria. Lactobacillus bacteria can tolerate acidic environments of pH 3.50-6.80 (LibreTexts, n.d.), with an op6mum pH of 4.50-6.50 (Śliżewska & Chlebicz-Wójcik, 2020). Moreover, the pH levels along the human diges6ve tract vary from the mouth, where saliva is present, to the point of exit in the large intes6ne. Generally, gastric juices in the stomach have a pH range of 1.00-2.50, the small intes6ne maintains a pH of around 6.60, and the large intes6ne has a pH of approximately 7.00 (Evans, 1988).

What prompted my explora6on was recognizing that bacteria have an op6mum range where they grow more efficiently. This recalled the behavior of enzymes, with an op6mal temperature and pH range at which they perform becer as catalysts. If these condi6ons deviate from the norm, enzymes undergo denatura6on, rendering them ineffec6ve as catalysts. Knowing this, my previous belief in the health benefits of consuming probio6c yogurt was shacered. I couldn't comprehend how, considering the challenging journey the probio6cs must undergo, being exposed to a wide range of pHs and specially the 2 acidic environment of the stomach, they could survive and fulfill the promised contribu6on to the microbiota in the large intes6ne. This explora6on aims to determine whether probio6cs can indeed survive and thrive when they reach the large intes6ne. The poten6al outcome of this research carries significant real-world implica6ons, especially in rela6on to the yogurt food industry and its claims of health benefits. Uncovering the growth rate of probio6cs through the diges6ve system at different pHs could reveal whether these claims are accurate or poten6ally misleading.

This inves6ga6on seeks to determine whether altering pH levels would lead to the inhibi6on of the bacteria cultures of probio6cs in soy yogurt by simula6ng the pHs found in the gut. To simulate the stomach and the wall of the large intes6ne, we will use nutrient agar plates containing different pHs to grow the cultures. The bacterial solu6on will be evenly spread along the surface and leg to incubate overnight. Subsequently, three samples will be taken from each plate, and the spectrophotometer will be employed to measure the absorbance of Lactobacillus in each sample, at a wavelength of 625nm. Higher absorbance values indicate a greater presence of bacterial colonies. Before the experiment, it is essen6al to carefully select, from the variety of available yogurts, one that exhibits the most efficient growth under overnight incuba6on condi6ons. As part of the preliminary work to this inves6ga6on, I examined various types of yogurts (soy yogurt, cow-milk yogurt, protein yogurt, and lactose-free yogurt) to determine which one prompted the highest growth of bacteria, and finally chose to work with soy yogurt.

A valid hypothesis would be that exposing the probio6c Lactobacillus to pH levels significantly devia6ng from the op6mal range of 4.50-6.50 will lead to a decline in bacterial growth because enzymes will be denaturing. While, in pH condi6ons far from 3.50-6.80, bacterial growth is an6cipated to be completely inhibited.

In this experiment, the independent variable isthe different pH levels to which the probio6cs are exposed. We will use pH levels of 2.00, 3.00, 4.00, 5.00, 6.00, and 7.00, achieved by adding hydrochloric acid (HCI) for acidifica6on or sodium hydroxide (NaOH) for alkaliza6on in the nutrient agar. To ensure a consistent pH throughout the agar, HCI and NaOH will be added and thoroughly mixed before the nutrient agar solidifies.

In this experiment, the dependent variable is the growth of probio6cs such as Lactobacillus found in soy yogurt, as measured by a spectrophotometer at wavelength 625nm. A spectrophotometer(Pasco wireless) is going to measure the light absorbed ager it passes through a solu6on; a higher number of cells in the solu6on, the higher the absorbance because more light is scacered (Phillips, 2023).

As a first approach, we tried two methods to culture bacteria from four different probio6c yogurts (cow milk yogurt, protein yogurt, soy yogurt, and lactose-free yogurt) to select the most suitable op6ons for our inves6ga6on. Ager using a streak method and dilu6ng the yogurt in dis6lled water on separate plates, the most substan6al growth (appendix table 6) was seen in the plates containing soy yogurt diluted in dis6lled water. Therefore, we have chosen this technique and yogurt for the experiment.

• Disinfect the workplace with 70% ethanol to minimize contamina6on.
• Sterilize eighteen Petri dishes with 70% ethanol.
• Label the Petri dishes, pH 2.00, 3.00, 4.00, 5.00, 6.00, and 7.00 for the soy yogurt’s bacteria, that grew the most.
• To prepare the agar for each pH (3 plates), mix 110 ml of dis6lled water with 4 scoops of infant formula in a beaker. Add 2 g of nutrient agar and 11 g of sucrose to the solu6on.
• Use the pH meter to confirm that they are at the desired pH. Add 1.0 M hydrochloric acid to lower the pH to the desired ones.
• Heat it in the microwave un6l completely dissolved.
• Pour each pH agar solu6on into three Petri dishes. A total of 18 petri dishes will be filled with agar. Let it solidify.
• Spread the previously collected soy bacteria (now in a 0.2 ml dis6lled water solu6on) into the agar plates. Add three drops to each agar plate.
• Use the sterilized metal spreader to spread the bacteria evenly on the agar’s surface.
• Incubate the agar plates at 28°C overnight.

• After the exposure period of 12h, remove the agar plates from the incubator.
• Cut with the edge of a test tube three equal size pieces of agar from each agar plate. For each pH we have three plates, so nine samples in total for each pH.
• Put each piece in a different sterilized beaker with 3 mL of dis6lled water.
• Remove the agar leaving the bacteria in the water.
• Use a spectrophotometer to measure the absorbance at 625nm of each solu6on, which indirectly measures the amount of probio6c bacterial growth ager exposure to different pH.

Qualitative - Petri dishes containing cultures with pH levels of 5.00 and 6.00 exhibited a consistently large, yellow culture at the center of the plates. Plates with pH levels of 3.00, 4.00, and 7.00 displayed a less dense, uniform culture on the surface of the agar. No visible change was observed in plates with a pH of 2.00. Furthermore, pH 5.00 plates displayed the presence of white dots.

The average of this data will be calculated for each pH to facilitate the iden6fica6on of pacerns. The equa6on for the mean is the following-

\(\bar x = \frac{\Sigma^{n}_{i=1}xi}{n}\)

Where-

\(\bar x \) -  mean
n - number of trials
i - the index

Calcula6ng the mean for pH 3.00 - 

\(\bar x\) = 0.235 + 0.219 + 0.171 + 0.234 + 0.238 + 0.224 + 0.234 + 0.235 + 0.172 9 = 0.218

The popula6on's standard devia6on will also be calculated to incorporate error bars on the average graph. A greater devia6on indicates lower precision in the data. The equa6on for the standard devia6on is the following-

\(\sigma = \sqrt \frac{∑((x_i− \mu)^2}{n}\)

Where-

σ - the standard devia6on

μ - the mean

n - the number of data points

\(x_i\)- each of the values of the data

Calcula6ng the standard devia6on for pH 3.00 - 

\(\sigma = \sqrt{\frac{\Sigma(x_i-\mu)^2}{9}}=0.027\)

The chart illustrates a consistent rise in Lactobacillus absorbance as pH increases. The curve starts at pH 2.00 with an almost inhibited growth of the bacteria. Due to the acidic condi6ons, a 6ny frac6on of the bacteria could survive to divide and increase the popula6on. From there, the graph follows a pacern of growth that persists un6l it reaches a peak absorbance at pH 5.00, ager which the absorbance begins to decrease. From there on, there is a progressive and slow decline in absorbance as the pH increases. The absorbance at pH 6.00 closely approximates the absorbance at pH 5.00 but diverges significantly from pH 7.00, which indicates the steady and notable decline starts at pH 6.00. The best pH to cul6vate Lactobacillus, based on this informa6on, is between 5.00 and 6.00. This was overly expected as the op6mal pH range of Lactobacillus is said to lay between 4.50 and 6.50 (Śliżewska & Chlebicz-Wójcik, 2020).

There is a considerable degree of uncertainty in the results, as indicated by the significant scacer represented in the length of the error bars, derived from the standard devia6on of the collected data. A likely reason for this could be acributed to the procedure itself. When immersing the agar pieces into 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 2 3 4 5 6 7 Absorbance ( ± 0.001AU) pH (± 0.01) Average absorbance for each pH 10 dis6lled water to detach the bacteria grown on the surface, some may have remained acached. This limita6on is acributed to the limited materials available in the school.

A T-test was conducted to assess whether a significant difference existed between pH levels, given the considerable overlap of error bars for each pH. A 5% significance level was adopted, assuming the hypothesis is supported by data with an expected error of a 5%. With 16 as degrees of freedom, the cri6cal value was established at 1.746. Acceptance of the alterna6ve hypothesis occurs when values surpass 1.746, indica6ng a significant difference between the samples.

The t-test shows that there is a sta6s6cally significant difference between pH 4.00 and pH 5.00, and between pH 4.00 and pH 6.00. However, between pH 5.00 and pH 6.00 the results may be due to chance, being non sta6s6cally significant. Addi6onally, between pH 5.00 and pH 7.00, and between pH 6.00 and pH 7.00 there is also a sta6s6cal significance. Between pH 4.00 and pH 7.00 the results are not significantly different. Both pH 4.00 and 7.00 fell outside the op6mal growth range, having similar absorbances as seen in the graph. This similarity explains the lack of significant difference between the results. Furthermore, the op6mal growth was seen by a plateau in absorbance at a range of pHs between 5.00 and 6.00, explaining the non-significant difference between these pH levels.

Overall, the pH values that were significantly different support the ini6al hypothesis that pH directly influences the growth rate of probio6cs.