cgualtieri's blog

Phototaxis is the directional movement of an organism towards or away from a light source. This behaviour has been observed in a wide range of organisms, from unicellular bacteria to complex multicellular organisms. Phototaxis can be positive or negative. Positively phototaxic organisms move towards the light source, while negatively phototaxic organisms move away from the light source. Each organism has its own specific biological cause for a phototactic response. The phototactic response of the common cellar spider in response to artificial light is a mechanism that is poorly understood. In this proposal, we aim to observe the phototactic behaviour of the common cellar spider using light emitting diodes (LEDs) arranged in six different controlled environments, and determine if the artificial light source has any effect on the spider's web building behaviours. To do this, medium, square, Ziploc Tupperware containers will be modified with LED lights and house one cellar spider for seven days. We propose six modifications of the containers to test the spiders phototactic behaviour in various environments:(1)Different lengths of LED light insertion in the container (2)Different colors of LED light displayed (3)Different spider species used (4)Different brightness of light displayed (5)Different time exposures of light and (6)No light present in the chamber. Phototactic behavior will be quantified by measuring the distance between the LED light and the spider web (if present) and its diameter. The data from all six environments will be compiled and analyzed using an Excel spreadsheet. Understanding the effects LED light has on phototactic responses of spiders, specifically web formation, will have profound implications on our understanding of animal behavior and pave the way for future research projects.

Before 2002, the dogma surrounding rod and cone cells was that they were the only cells with photosensitive properties in the retina of the eye. It was also known that light entrainment and the circadian cycles are tuned by environmental influences. Scientists knew that exposure to different light cycles can reset the circadian clock, but did not know how this worked. Humans and mice that lacked rods and cones could still reset their circadian rhythms. They hypothesized that there must be another mechanism in the eye besides rod and cone photoreceptors to allow for this photosensitivity. Their question was: Could melanopsin be a photo pigment protein that allows retinal ganglion cells (RGC’s) to be light sensitive?

Observation of a colony from the pasteurized plate, under a phase contrast microscope at 1000x, showed endospores inside rod shaped bacterium. The endospores were located primarily at the terminal end of the bacillus, and were seen as bright ovals with the darker bacterium surrounding them. This confirmed that the bacillus containing endospores survived pasteurization and was able to continue growing on the nutrient agar. Not all of the bacilli contained endospores, suggesting that the nutrients on the agar were substantial enough to inhibit sporulation. These bacilli grew in diplobacillus and streptobacillus arrangements. A Gram stain of the same colony used for microscopy showed that the endospore forming bacilli were gram positive based on the dark purple color of the bacterium. The endospores were not stained and appeared as clear ovals at the terminal ends of the bacterium. This Gram stain confirmed that the bacterium that formed the endospores were Gram positive. Also, the Gram stain showed that the thick layer of proteins and peptidoglycan surrounding the endospore had not been damaged and was able to keep the stain and water out of the endospore.

I took a statistics class in my sophomore year, and remember it being a very different learning experience compared to the biology classes I was taking. I remember using Excel frequently, and learning lots of formulas to use on the data we entered into the spreadsheet. I remember we focused on simple random sampling, which was the probability that an item is selected for a sample is the same for all population items. We made lots of graphs, including histograms and bar charts to visualize the data we had collected. I remember we learned about the two different types of data, qualitative and quantitative data. We also learned the difference between a discrete and a continuous variable.

In the Fall 2018 semester at the University of Massachusetts Amherst, students in Professor Brewer’s Writing in Biology class constructed a methods section to describe how they created a multi-panel figure containing photographs of a spider web located somewhere on campus. The methods were then given to another student who was to follow them and reconstruct the original figure. Analysis of the observational differences between the two figures yielded several similarities and differences between them. Similarities between the figures clearly showed which parts of the methods section were well written and able to be reconstructed. These included the location of the web, the photographs of nearby buildings, and the layout of the figure. The layout of the two figures was nearly identical, consisting of a four panel figure labeled A-D in large black letters with a white background. The differences between the figures could be attributed to the lack of clear instruction in the methods with regard to the camera angle, camera location, and precise location of the spiderweb in relation to nearby landmarks. The figures differed from each other in several ways. First, the angles that photos C and D were taken differed significantly. Second, the location of the superimposed white circle meant to identify the location of the spider web was on the wrong side of the handrail in the replicate figure. Third, the formatting of the letters labeling the four photographs in each figure differed between the original and replicate figures.  The factors that contributed to these differences between the figures include specific details being left out of the methods regarding camera angle and camera height while taking the photographs. The location of the superimposed white circle identifying the spider web was clearly outlined in the methods section, so human error was a potential factor in the misidentification of the spider web’s exact location. Lack of detail about the font size, shape, and boldness were also absent in the methods which led to differences in figure labels. This paper outlines in detail the observational differences between two figures that were constructed using the same set of methods, and describes the most likely reasons for these deviations.

This experiment used spectrophotometry to measure E. coli growth at four different temperatures (27°C, 37°C, 45°C, and 55°C) over the course 75 minutes. The aim was to measure cell numbers by measuring the turbidity of samples inoculated with E. coli. Growth rates and generation times were then obtained using the data collected. It was expected that the E. coli would have the highest growth rate and shortest generation time at 37°C. This temperature is most similar to E. coli’s natural environment, the human intestinal tract. At 37°C, E. coli should spend a substantial amount of time in the exponential phase of bacterial growth, and have a prolonged stationary phase before entering a period of cell death. The E. coli grown at 55°C were expected to show a decreased growth rate and a longer generation time. At this temperature, proteins and other cellular components become denatured and cell lysis occurs. It was expected that E. coli grown at 45°C would have a growth rate and generation time in between that of the 37°C and 55°C samples. At 45°C proteins should not become denatured and most cells will not lyse. The increased heat was predicted to slow cell metabolism and mitosis enough to distinguish a difference in growth rate and generation time compared to the 37°C sample. The last sample, grown at 27°C, was expected to show a lower growth rate and higher generation time compared to the three other samples. At this lower temperature, the metabolic processes of E. coli were predicted to slow significantly, which would reduce the number of new cells forming and increase the generation time by slowing mitosis.