Category Archives: Week 2

An ELPnation [Explanation] of My Project

My research project for this summer will be to analyze various elastin-like polypeptides (ELPs). ELPs are polypeptides that incorporate the 5 amino acid long sequence of Val-Pro-Gly-Xaa-Gly, where Xaa represents an unspecific amino acid. ELPs are a kind of artificial intrinsically disordered protein (IDP), which are proteins that do not fold in the typical way but rather maintain an unfolded (disordered) form that permits multivalent behavior. ELPs also change phase with lower critical solution temperature behavior, which means that they will be soluble below a critical temperature and phase separate at/above it.

So far, I have worked on cloning recombinant plasmids that contain part of the desired ELP sequence with E. coli. Each ELP sequence has an “A cut” and a “B cut” plasmid which will be ligated together in order to get the desired sequence. This is done because ELP sequences are quite repetitive and this makes it difficult for manufacturers to directly make it. E. coli is also used in order to generate the protein from the plasmid. Flasks of E. coli are given the plasmid and reproduce until they almost reach carrying capacity, at which point they are given a treatment to induce protein synthesis. This is done in order to maximize yield as a flask well below carrying capacity would not be able to produce as much protein and one at carrying capacity would not be as metabolically active. 


Sleep disruption due to prenatal environmental toxin exposure and neurodevelopment disorder pathology

The prevalence of neurodevelopmental disorders (NDDs), such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), has increased rapidly over the past two decades. As such, much research has gone into the root causes and mechanisms of these disorders. Previous studies on the genetic roots of NDDs have identified several alleles associated with NDD pathology, however, prenatal environmental stressors and toxins are thought to contribute greatly to this recent increase.

Sleep plays a critical role in synapse remodeling, especially during adolescence. Astrocytes, a type of glial cell essential to regulating neuronal activity, have recently been shown to modulate the sleep-wake cycle. Specifically, astrocytes seem to regulate both depth and duration of NREM sleep. Previous work has shown that sleep appears to be particularly sensitive to environmental stressors and toxins. 

In the case of neurodevelopmental disorders, such as autism spectrum disorder, sleep disturbances are observed in nearly 86% of patients. Thus, the project I will be working on this summer aims to investigate the mechanisms by which prenatal exposure to environmental toxins impacts the development of neurodevelopmental disorder pathology. 

In my mentor’s previous work, she identified that a prenatal combined diesel exhaust particle and maternal stress (DEP/MS) paradigm results in neurodevelopmental disorder pathology in offspring. 

Using this mouse model, we plan to address two main questions. Firstly, how does prenatal exposure to maternal stress and environmental toxins impact sleep patterns in offspring? Secondly, do we observe changes in gene expression patterns and astrocyte physiology in the brains of these mice?

We’ve begun by using electroencephalography (EEG) and electromyography (EMG) to analyze sleep patterns in DEP/MS mice offspring. By doing this, we hope to determine how time spent in NREM and REM sleep differs between control and DEP/MS mice. We then plan to isolate RNA from frontal and parietal cortical astrocytes in order to analyze gene expression patterns through quantitative real-time PCR. Additionally, building on the sex differences in NDD pathology observed in my mentor’s previous work, we plan to use the forced-swim test to measure depressive behavior in DEP/MS mice.

Marco Polo: How Do Lichen-Forming Fungi Find Their Cyanobacterial Partners?

This summer, I will compare lichenized cyanobacteria communities to environmental cyanobacteria communities (cyanobacteria living outside the lichens) to inform how lichen-forming fungi associate with their cyanobacterial partners. For context, lichens are organisms made of symbiotic associations between algae/cyanobacteria and fungi. Fungi in lichen can reproduce sexually via fungal spores, which are essentially sterile, free of cyanobacteria, and it is largely unknown how the fungi find and associate with their symbiotic partners. In nature, fungal species have been observed associating with different cyanobacterial species, sometimes “switching” between cyanobacterial partners. The mechanism behind symbiosis formation is unclear; it is unknown where and how often the fungi find their cyanobacterial partners, and we want to know if the same cyanobacteria are found in the surrounding environment. 

My project focuses on lichens made of Peltigera, a genus of lichen-forming fungi, and Nostoc, a genus of blue-green algae or cyanobacteria. Using lichen and environmental samples, we want to ask: are lichenized cyanobacteria similar to, or different from, the environmental cyanobacteria found outside the lichens? The Lutzoni Lab collected lichen and environmental samples across Alberta, Canada, to help answer this question. The lab collected roughly 2500 lichen samples and 1800 environmental samples across 15 sites spread over five natural regions of Alberta (3 sites per natural region). The environmental samples consist of substrate sampled next to and between lichens and are split into 900 “top” and 900 “bottom” samples. The top samples were collected closer to the earth’s surface, and the bottom samples were collected deeper underground. 

This summer, I aim to answer two primary questions to determine the best method for extracting and sequencing the Nostoc DNA from lichen and environmental samples!

First, we want to know if the 16S rRNA or rbcLX gene is a more accurate marker for detecting Nostoc in the samples. The rbcLX gene is more specific to cyanobacteria and has more variation than the 16S rRNA gene, so it could more accurately classify between species of Nostoc. However, Nostoc contain one copy of the rbcLX gene compared to multiple copies of the 16S rRNA gene. The environmental samples may have low abundances of Nostoc, so sequencing the 16S rRNA gene may be more suitable for detecting the low cyanobacteria levels. To answer this question, we are testing the 16S rRNA and rbcLX approaches on 12 environmental samples which have already undergone metagenomic and metatranscriptomic analyses. By comparing the resulting 16S rRNA and rbcLX sequences to pre-existing data, we will select the marker with which we will sequence the remaining environmental samples. We hypothesize that 16S rRNA will more accurately detect the Nostoc because we are trying to detect microbes presumably in trace amounts, and because the 16S rRNA gene is the standard marker in microbiology. 

Next, we want to determine how the cyanobacterial communities in the top environmental samples compare to those of the bottom. As mentioned above, the 900 top and 900 bottom samples are from the same areas but different depths into the substrate. We want to see if the bottom cyanobacterial communities are a subset of those of the top samples, and if so, only extract DNA from the top samples to save time and money. We hypothesize that the bottom samples will be a subset of the top, and more Nostoc will be detected in the top samples because Nostoc require sunlight to photosynthesize ☀️

Lots and lots of lichen samples! 6/14/23

Project MutaLib

Four different bases can be stringed together in a mind-boggling amount of variations. They form one of twenty amino acids that themselves can be combined to form various proteins. My project indirectly supports my lab, Neurotoolbox, in its endeavor to improve fluorescent proteins that are utilized for spatial and temporal resolution of neurons in the brain. There are two notable types of proteins that the lab uses. One protein can be used to activate a neuron by shining a light with a specific wavelength. The other protein can fluoresce upon activation by its respective neuron. Both of these proteins have numerous capabilities in the field of neuroscience and in identifying nerve tracts.

My project within this lab is to facilitate the pursuit of improving the biological capabilities and optimizing the performance of these proteins. My principal investigator, Yiyang Gong, provided me with a MATLAB dataset housing all the reads of a mutation-induced sequence of one of the aforementioned fluorescent proteins. There are over 350,000 different mutated sequences each with their respective coverage (number of reads/voters) and quality scores. The original sequence is known, but the issue is the successful discernment of true and fake mutations. Over 55% of the dataset has incredibly low coverage (1 or 2 reads), 15% has moderate coverage (3 reads), and the other 30% has high coverage (4 to 20 reads).

When there are few voters and an inconclusive quality score, what is the true mutation? What about if both reads have a perfect quality score yet they disagree? These are the questions I have to answer, notably when the coverage is only moderate to low (3 or less) which makes up 70% of the dataset. Through Python data analysis, probabilistic modeling, and machine learning applications, I need to clean the dataset and create a library that associates a barcode (tagged to the end of different mutated sequences) with its respective SNPs. The mutations would later be processed to determine which sets of mutations would improve the performance of the fluorescent protein (my next project after completion of this one).

A Talk with the PI

Dr. Mike Tadross has always liked tinkering with things and looking to solve difficult problems. For his undergraduate years studied to become an electrical and computer engeerir at Rutgers. He liked electrical engeering because of viewing circuits as puzzles that he could solve.

After undergraduate he started his work on M.D. P.H.D in Biomedical engeering at Johns Hopkins. His P.H.D ended up taking three years longer than he expected because of a project that he could not get to work. This project has still yet to be solved. Following his P.H.D he started working on DART (Drugs Acutely Restricted by Tethering) before he had an established lab of his own. After the publication of paper with DART he was offered a faculty position at duke and to establish the Tadross lab. The Tadross lab focuses on making tools to study the brain whether that be chemical or electrical wiring. He believed that since the brain and computers are composed of circuits then one would be able to design computers to interact with each other. He came to the conclusion that one needs to be able to put all of pieces together to understand the brain. Dr. Tadross when putting together his lab embraced this. He brought in people that focused on the chemical, electrical and the biology of the brain.

His path has not been as linear as one would expect. At Johns Hopkins, he joined a lab that focused on a topic that was not particularly interesting to him. During his time in the lab, he would spend three years on a project that would never actually end up working out. Because of this he worked on a project that he was not particularly interested in, but this gave him the experiencing failure firsthand in the lab. After graduate school, he worked in a pre-faculty position where he was able to work on his own projects but did not have his own lab. This eventually led to him figuring out his greatest invention using halo tag technology to restrict binding for drugs nears the channels.

Talking with Dr. Tadross, I had learned that if you are flexible and are willing to work hard that you will eventually stumble upon success. That while diving deep into topics is important having a broader understanding of what is occurring at all levels is just as crucial. Overall, my talk with Dr. Tadross made me more comfortable and adjusted to his lab.

Aches and Pains

The lab I’ve been working in has an overarching focus on pain signaling and sensory plasticity, which covers the wide range of interests of all of the lab members. Working in Dr. Ji’s lab has made me appreciate the complexity of pain, from the different types, like chronic vs acute, to the vast amount of biological and molecular pathways involved. The sheer amount of research being done and research that still has to be done is close to overwhelming, but working with my research mentor, Dr. Junli Zhao, has helped me focus in on a specific area that I can contribute to. Dr. Zhao primarily studies the PD-1 gene and its various roles, especially in pain signaling.

My project builds off of previous research conducted by the lab as a whole, and observations made by Dr. Zhao. We are examining the impact of the gene encoding the programmed cell death protein 1, or PD-1, on chronic pain-induced anxiety and depression, as well as cognition. The primary methods we are using are mouse models, in which we will first induce a chronic pain condition using a spared nerve injury, or SNI, then use a wide variety of behavioral tests to measure the anxiety and depression levels in the mice, as well as their pain levels and cognitive abilities. We will also examine the expression of PD-1 in the brain, particularly the amygdala, which has been found to play a role in anxiety and depression. This examination of PD-1 expression will be conducted through the use of immunohistochemistry and RNAscope.

Lab Rats…

Every 40 seconds, someone has had a stroke in the United States [1]. This occurs when an obstruction in the blood vessels prevents the brain from getting ample oxygen and nutrients, causing a cavity of dead tissue in the brain. This brain tissue has a limited capacity to regrow, and the resulting cavity is lacking in blood vessels and neuronal connections.

The Segura lab is leading in this work, as they’ve come up with various hydrogel networks that carry growth factors (amongst other things) to promote the regrowth of this dead brain tissue. We use mice–model organisms–to study the impact of these gels, meaning I give a bunch of mice some strokes for the greater progress of science. I’ve been part of over 60 mice surgeries since I’ve been in the lab, and the general process includes anesthetizing the mice, injecting a substance to induce the formation of free radicals that can cause blood clots, projecting a laser onto specific portions of the open skull to induce stroke, and injecting the hydrogel into the stroke cavity a few days later. The mice are only partially impaired, and seem active immediately after inducing strokes, unlike human patients who need countless rehabilitation and medical attention. The mice will be sacrificed at predetermined time points and brain slices will be studied to determine the impact of the gels on the regeneration of blood vessels and neuronal growth.

I’m excited to be a part of this lab and collaborate with other researchers to study strokes. Blacks are twice as likely to have strokes than whites and have the highest death rate afterward [2]. I know of at least four people in my family who’ve had strokes, so this research hits close to home. I also hope to shadow some behavioral studies at the lab with the aims of studying the impact of strokes in general, as well as the use of hydrogel on the behavior of the mice. I’m just really happy to be a part of the Segura lab!

The Path(ogen) Less Traveled

Before I was dropped off at college, I distinctly remember the ominous warning from my mother: be careful, don’t get meningitis! The disease is known for occurring in infants and college students, but I didn’t really know what it was…until this summer, now that I’m studying it. While there are several pathogens that are able to cause meningitis, Dr. Perfect’s lab studies Cryptococcus neoformans, or the fungal pathogen readily found in the environment causing cryptococcal meningitis. Though its environmental ubiquity seems alarming, Crypto. is actually an opportunistic infection, meaning it only causes disease when it is able to take advantage of weakened immune systems, such as those with HIV/AIDS, transplant recipients on immunosuppressants, or possibly even survivors of COVID-19. Even so, the prevalence of cryptococcal meningitis is significantly higher in poorer countries with less access to necessary treatments and supplies. Duke Hospital’s own survival rate for Crypto. infections is around 80%, while the global survival rate is only 50% (skewed largely by the populations lacking in adequate healthcare resources). Despite this frightening statistic, research on Crypto. is largely underfunded due to the fact that cryptococcal meningitis is a noncommunicable disease, or it cannot be spread person to person via a cough or a sneeze the way that the flu, COVID-19, or other common diseases can.

Luckily, Dr. Perfect’s lab is doing the hard work, spending every day working towards understanding Crypto. and trying to find new ways to target it through drugs and other methods to help prevent or cure future cryptococcal meningitis infections. This is where I come in (with my bench mentor/graduate student Julia, of course). One of the most interesting things about Crypto. is where it causes infection: the brain/spinal cord. A vast majority of other pathogens struggle significantly with the lack of nutrients and overall harsh environment of cerebral spinal fluid in the central nervous system, which is why Crypto. is such an intriguing fungus; where others fail at mere survival, Crypto. seems to thrive in this nutrient-deficient environment, hence its deadly survival rates. One project I am helping work with Julia to look at this summer is one particular set of genes that may be influencing this growth. These genes regulate nitrogen catabolism, or the identifying and processing of available nitrogen sources for use. Nitrogen catabolite repression (NCR) is the name for the regulation of these genes via certain regulators based on the nitrogen sources available (normal, easily metabolized sources results in a negative regulation — turning the genes off — and sources that require several steps to break down cause a positive regulation response — activating the genes encoding for certain necessary enzymes to break the nitrogenous compounds down –). Our first steps so far have been looking at two potential NCR genes, tagging them with a fluorescent tag (we are using mCherry, but for comparison it’s like GFP), and looking for any interactions between the proteins based on localization (if the proteins are co-localizing, we will see a certain fluorescent pattern showing them near each other). Knowing if these genes work together to regulate nitrogen catabolism is critical for moving forward in the overall investigation of identifying these regulation pathways in Crypto.

These last two weeks, we have been assembling all the necessary pieces to create the tagged strains of Crypto. I first had to design primers that would work in a PCR reaction to amplify each of the 5 segments needed for the tagged strain (the 5’ UTR, for attaching to a plasmid backbone, the NAT antibiotic resistance cassette, for incentive to integrate the plasmid into Crypto., the promoter + gene itself, the mCherry fluorescent tag, and the 3’ UTR region to attach to the other end of the plasmid backbone). The PCR results so far have been mostly successful, with two stubborn fragments still left to successfully amplify (let’s just say I’ve run a LOT of electrophoresis gels this week). Once we know that the PCR worked, we cut out the bands and extracted the DNA from them to be saved until all the pieces are ready. This week, we are finally going to do a Gibson assembly to put all the puzzle pieces together.

These two weeks so far have been a whirlwind of reading papers and learning techniques and working towards an exciting goal; I feel like a supersaturated sponge, but I can’t wait to keep learning more!

My first (of many) electrophoresis gels showing the successful PCR reactions for gene 1: URE3. Our 2nd fragment had the best band, meaning it worked the best (NAT cassette), and was extracted, but most of the other four fragments had to be run again in a new PCR reaction.

This was the gel electrophoresis showing the PCR reactions for gene 2: TAR1. The brighter bands were the successful amplifications, and the ones that were very faint or didn’t show up at all in the column had to be run again. Here, we were able to gel extract from 1 and 2, and some from 3 and 4 (This was a vast improvement from the first URE3 gel, which was one of the first PCRs and gels I ran in the lab).


From Generalized to Precise

Genetics intrigues me because of its ability to explain the mysteries of biology. It helps us understand the biological programming behind all life forms, including ourselves. In the past 100 years we have discovered DNA, developed ways to read it, and now we are working on methods to write and edit this code. It is the growing understanding of the universal language of life that provides us the incredible power to shape the future of humanity. This is a scientific revolution that, with the right amount of careful consideration, will change the human condition for the best. Most obviously it will transform healthcare. 

A person’s healthcare treatment today is based on what works for the average human in a population of 7 billion. But with the decreasing cost of genome sequencing and a better understanding of the genome itself, a person’s treatment is becoming increasingly based on their biology. Healthcare is therefore beginning to shift from generalized to precise. 

One of these novel precise treatments is gene therapy and the researchers at Asokan Lab work to find novel ways of improving it. Gene therapy is a technique that targets the cause of the disease by finding genetic solutions for genetic disorders. The classic model of gene therapy is to use a viral vector to deliver a working copy of a defunct gene. The introduction or change of genetic material into the cells of a patient is all about changing how a protein or group of proteins is produced by the cell. For example, one of the genetic disorders targeted by the project I’m currently working on is Duchenne muscular dystrophy (DMD). Patients with DMD have severely reduced muscle strength as a result of alteration to a protein called dystrophin that helps keep muscle cells intact. The goal of the project I’m working on is to increase levels of functional dystrophin expression in DMD patients through RNA editing. 

The central dogma of biology is that the pattern of information flow in our cells goes like this: From DNA to new DNA (DNA replication), from DNA to new RNA (transcription), from RNA to new proteins (translation). RNA gene therapy targets disease-causing mutations at the translation step. In our project, we aim to edit RNA via trans-splicing by manipulating the splicing pathway by which pre-mRNA turns into mRNA. In doing so, we can replace a mutant exon in the DMD mRNA transcript, which is known to abolish dystrophin production, with a functional version of that exon. When this correction is made, therapeutic levels of dystrophin restoration can occur. DMD is only one of the multiple genetic disorders we will be targeting with this RNA editing mechanism. I’m very excited to be working on a project with this level of therapeutic novelty and medical relevance.

Brain Circuits of Habit and Goal Directed Behavior

What do you think creates a habit? Habitual behaviors are defined by learning  an automatic response to a certain stimulus. For example, you could have breakfast in the morning, even if you are not feeling particularly hungry at the time. Here, the action(having breakfast) is executed regardless of the goal(consume calories to feel full), but instead follows a learnt stimulus(time). Thus, habitual behaviors are not conducted for the aim of fulfilling a goal, but is dependent on the stimulus.

Calakos lab investigates the cellular and circuit changes in the brain(with a focus on striatum) as a behavior changes from goal-directed to habitual. This can be done by overtraining, where an initial goal directed response to press a lever to obtain food pellets becomes habitual/automatic over repeated trials. In this case, the point when the researcher knows the behavior is no longer goal-directed is when the mouse still presses the lever with same frequency, regardless of whether it was full or hungry before the behavioral test. This is called the devaluation test as you devalue the utility of the outcome.

Striatum is a brain area known to be involved in not only initiating or inhibiting movement, but also changing from goal-directed to habitual behavior. My research project is to image the afferent connections into the DMS and DLS-dorsomedial striatum and dorsolateral striatum- using retrograde tracer AAV. Active brain circuits during goal-directed and habitual behavior will be selectively labeled, which would be used to compare how the inputs into the DMS and DLS changes as lever press behavior turns from goal to habit.

Chromatin Affects the Sex Drive of Flies

The project that I am working on in the Volkan Lab fits neatly into one of the lab’s broader questions: how chromatin regulation around master genes affects behavior. In regards to the fruit flies I will be studying, the behavior in question is male courtship and the master gene I will be looking at is called Fruitless, or fru. This fru gene transcribes a transcription factor that has been found to be the primary effector in the development of appropriate courtship rituals in male flies.

My specific project is to try and find the mechanism through which peripheral sensory systems affect courtship behavior. The sensory system I will be studying is a particular receptor in the olfactory system called IR84a. This receptor is responsible for sensing (and be activated by) phenylacetic acid and phenylacetyl aldehyde, two chemicals that are found on the fruits and plants that the flies use as oviposition sites and food sources. Upon exposure to these chemicals, and thus activation of the receptors, male fruit flies experience increased courtship behavior. In addition, when mutants are made that lack the IR84a receptor, the male flies not only lose their ability to sense these aphrodisiacs but they also display a lowered base courtship rate compared to wild type male flies. These two phenotypes clearly demonstrate IR84a’s link to courtship.

Studying IR84a ties into the overall question of the lab because we hypothesize that the mechanism through which IR84a affects courtship behavior is by regulating the chromatin state around the master gene fruitless. A process called ChIP, Chromatin Immunoprecipitation, will be performed to assess the chromatin state around fruitless in both the peripheral and central nervous systems of both IR84a mutant and wild-type male flies. If there is a difference between the two chromatin states, then this will provide evidence in favor of our hypothesized mechanism.

Dopaminergic Neurons: That’s Pretty Dope

First full week at the Mooney Lab: complete. What can I say, this week has assuredly presented some steep learning curves. From accidentally sacking my bird (an affectionate euphemism I suppose) during a brain injection surgery to being unable to find the left ventricle during a perfusion (the process of draining the blood from a sacked bird), this week has posed many challenges. Nevertheless, learning all of these techniques and being thrown into the deep end of neurobiology research is quite exhilarating. I constantly find myself thinking, “Woah, this is sooo cool! (for lack of better words haha).” 

In the short time I have spent with the lab, I am by no means an expert on the project I am about to conduct; however, I will try my best to explain it here. Yet, before I do that, I think it will be helpful to define a few terms (learning these definitely helped me in understanding my project):

dopaminergic neuron cells: a class of neurons that synthesize the molecule dopamine

tyrosine hydroxylase (TH): enzyme that is essential in the synthesis of dopamine; all dopaminergic cells will have the TH enzyme

VTA/SNc: areas located in the midbrain of the zebra finch that are noted by a high concentration of dopaminergic cells

green fluorescent protein (GFP): protein that fluoresces green when exposed to certain wavelengths of light; commonly used as a reporter of gene expression

For my project, I will be testing whether a new cell editing technology is functional and expressed in the dopaminergic neuron cells of the zebra finch. For proprietary reasons, I can’t say the name or describe exactly how this new technology works. However, at a surface level, the technology is able to recognize and bind to a chosen RNA sequence within a cell (in my specific case, it is the sequence that encodes the TH enzyme for dopaminergic neurons). The technology also contains the sequence for GFP. If the technology successfully binds to the TH sequence, then GFP should be expressed. To test this, I will surgically inject the technology into the VTA/SNc region of the zebra finch and “let it sit” for around a month. After this waiting period, I will sack the bird and analyze the dopaminergic neurons within the VTA/SNc and determine if the technology was successful. 

So, in a nutshell, that’s my project! Right now, I am familiarizing myself and learning how to conduct all of the necessary techniques. So, I still have a little time before I actually start the experiment. For now, it’s just learning surgical procedures and how to do bird haircuts (yes, it is exactly what it sounds like).

Novel Nanoparticles

If you were to ask me a week ago what a nanoparticle was, I’d give a pretty generic answer saying that it was something really small. While that statement is true, there is so much more to these microscopic specks than we understand. One of the biggest problems in drug development is the issue that not all compounds are soluble in water. Not being able to be dissolved means it’s hard for the body to absorb the medicine that you are trying to take. There is also the issue of directing the drug to its intended target. A potent liver drug isn’t useful if it accidentally makes its way into your heart. These two issues can be solved with nanoparticles.

Research into the design of different types of nanoparticles has shown promise, but often results in a combination of a difficult manufacturing process and a low, around 5-10%, drug-loading capacity. The Reker lab is taking a novel approach to form a different kind of nanoparticle. Our nanoparticles rely on the natural tendency of select molecules to aggregate together and form clumps. These “clumps”, really nano-sized clusters, of drug and excipient pairs have a revolutionary potential for up to 95% drug-loading capacity. They are also significantly easier to manufacture than traditional nanoparticles. My project this Summer is building off of Dr. Reker’s previous work in order to find a potential treatment for Covid.

Imagine a conveyor belt in a car factory. All of the different parts for the car go along the belt, and are assembled into larger parts at each stop. My day-to-day involves working at one of these stops. Currently, my “stop” on the conveyor belt deals with simulating the potential interactions of drug-excipient pairs of interest. I get a pair found from a machine learning model, run some code, generate a simulation, and then analyze the simulation and see if it shows promise for a nanoparticle to form. It’s a pretty straightforward process, until you realize that the simulations can take hours to generate. Simulations are also an approximation of what could happen in reality, not necessarily what will happen. This approximation can be made better by fine-tuning the generation parameters. Part of my job is to find the “sweet spot” combinations that most accurately reflect what would happen if we were to make the particles in the lab. Eventually, if I find a combination that shows promise, I will get the opportunity to try synthesizing my own nanoparticles.

While most of my research has been dry work, I’m starting to find analyzing the simulations fun. Seeing all of the cool movies from visual representation is satisfying. I also do some analysis on intermolecular interactions, but that’s more numbers-based. My experience so far has been filled with all of the things that I like about science. There is so much overlap with this project in particular. I need to understand how the code runs in order to generate simulations, I need to know how to code in order to analyze the intermolecular interactions, I need to have a good understanding of chemistry to make sense of the simulation, and I need to have an open mind as it’s only me and my mentor working with this pipeline. We are the pioneers in this space. It is up to us to find the optimum parameters and develop analysis techniques ourselves. It’s both intimidating and exciting being alone in this space, but I’m loving the journey so far and I can’t wait for what the future holds!

This is one of the cooler simulations I’ve run. Normally, the particles form clumps with each other, but this one has excipient molecules on vertices of the drug cluster forming a starfish shape.

Reinnervation and Revascularization of Engineered Skeletal Muscle

In 2006, a Japanese researcher named Yamanaka discovered a chemical concoction which would allow the dedifferentiation of fated cells to once again become induced pluripotent stem cells (iPSCs). This discovery had significant impact in the world of regenerative tissue engineering, as it allowed for the indefinite creation and proliferation of complex cell types cultured from the patient’s own cells. In particular, the Bursac lab under which I am currently researching studies how iPSCs can be used to specify functional synthetic myocytes, both skeletal and cardiac. However, the large roadblock in tissue engineering research currently is that tissue fated from iPSCS are not able to generate as much force and muscular volume as primary myocytes.

The projects I am working on seek to better understand the roles that vascularization and innervation play in the development of functional skeletal muscle tissue, and more importantly, how co-culturing endothelial cells or neurons can allow muscles to exhibit greater forces. As one may expect, working with cell cultures are very demanding and requires a comprehensive set of procedures to ensure the growth and differentiation of each tissue type, as well as the necessary processing in order to understand the capabilities or functionality of the cells.

Although I’m only one week in, I’ve definitely picked up a plethora of laboratory techniques which were necessary in order to cover all aspects of an experiment. I learned how to create 2D and 3D growth media which facilitates the growth of cells within the first week of culture. After this, the cells will spend 2-3 weeks in a differentiation media which causes them to fuse and interact with each other and form tissue. It is during this step where endothelial/neuron cells will interact closely with the formed myofibers and form supporting vasculature or neuromuscular junctions. To understand the state of the muscle fibers at different points of the experiment, the tissue can be used in many ways. One of the most important of course is force testing, in which we rig bundles to a sensitive force guage and electrically stimulate them to understand their impulse responses or tetanus response. Another common way to understand the bundles is to do cross section stains, which requires the use of the cryostat machine I described last week, or whole bundle stains under which the entire skeletal muscle tissue will be imaged. Another procedure would be to use whole bundle RNA isolation which allows for the analysis of RNA expression at some week to better understand the genetic effects the presence of supporting cell types may have on muscle development. Additionally, we may use qPCR to quantify the relative amounts of certain genes and which ones are expressed more than others.

Although it sounds simple, there are inherent limitations to such research. For one, cells are fickle and it is difficult to understand why an experiment may go awry or why cells may behave differently, and these fluctuations can only be mitigated through strict sterilization practices. Additionally, the growth cycles for engineered tissue take weeks to months to produce tissue, which is currently ineffective for clinical application. However, I am optimistic that the research I am doing will allow for us to take one step closer to the goal of quick tissue regeneration and integration to save victims suffering from dire wounds.

ELPs: A New Vehicle for Drug Transportation

The field of drug therapy and molecular engineering is constantly changing and exploring new options to improve efficiency. One main issue when creating new drugs is controlling how long it can stay in someone’s system before it is removed, as well as accuracy. Many research labs have begun looking into new polymers, especially ones that can be grown in bacterial cultures, to assist in the transportation of drugs. I am working this summer in the Chilkoti Lab to investigate a biopolymer that is being tested as a future drug delivery option.

My main project involves assisting my lab mentor, Anastasia Varanko, in growing and harvesting elastin-like polypeptides. Also known as ELPs, these polymers can be grown in bacteria and have a unique property of changing solubility based on temperature. When it is at lower temperatures, it becomes more soluble, and at higher temperatures it can become insoluble. This temperature threshold can be modified through molecular engineering, and allow scientists to control when it aggregates. It is then possible to keep the ELP at a lower temperature for first injecting the drug, and after entering the body it can become insoluble and extend its circulation in the blood. This leads to an overall more long-lasting and efficient drug. Other proteins can also be added to the ELPs, which may be utilized to transport proteins into the body. This includes receptor blockers that can inhibit or enhance different pathways. 

My main focus will be collecting ELPs from bacteria and purifying them, as well as attaching different proteins to the ELPs using transformation on bacteria. I look forward to continuing my work in the lab throughout this summer and hopefully creating a stable protein that can be used for future drug applications.

More Than Meets the Eye

My research project involves studying a particular type of pitcher plant called Sarracenia purpurea. These carnivorous plants have leaves that form pitcher-like structures that are able to collect water. This water, however, hosts a community of microorganisms that digests any prey that falls into these pitchers. The waste excreted by these organisms can then be taken up by the plant. 

This research project involves taking trips to various locations where these plants are found. We will be taking samples of the fluid in the pitchers as well as taking clippings of the leaves. The fluid will be studied to see what types of prey the plants are catching, what organisms live in the water, and what enzymes are present. Furthermore, nitrogen analysis will be conducted on the plant’s leaves. So far, we have visited and surveyed about half of the sites we will be sampling from, and we will soon begin sampling and studying these complex plants.

Although these plants may seem simple and uninteresting, there is much more to them than initially meets the eye. Within these plants lives an entire food web, and, even though the interactions within the food web will be studied on a small scale, learning about these interactions can help us understand those that occur at a much larger scale.

Piecing Everything Together Now

From all the bits of information my mentor has shared with me, some going over my head and some pasted on my head after mentally repeating it over and over, I know my project is about measuring the drug tolerance and resistance of Cryptococcus neoformans to different concentrations of Fluconazole (FCN). We’re using several strains of Crypto. to effectively take account of all possible outcomes.

At this point, I’ve grown the different strains of Crypto. in solid media (YPD + NAT 100 + CM 100) and liquid media (Liquid YPD + 1X Hogness), which took 3 days for each, and have inoculated the fungi cells in the solid media onto a new liquid media plate, which, after growth, will then be inoculated again onto the plates with different concentrations of FCN. I have only done this for the 96 well plates and plan to repeat this process with the 364 well plates. Once the inoculation onto the FCN concentrated plates begins, I will need to record the growth with a scanner for several days.

With the recent increase in Cryptococcus meningitis in several countries, this research will be a valuable contribution in discovering the most suitable method in treating Crypto. meningitis. It has already been found that the capsule size of the FCN-resistant isolates is not largely impacted by fluconazole in comparison to the sensitive isolates; thereby, sustaining its virulence. Still, in a 2016 study, the growth of those same FCN-resistant isolates at 37°C was observed to be reduced. This means that although the fungi is resistant to the drug, the isolates’ growth and its morphology is impacted by its Fluconazole resistance (Rossi 2016) . With this in mind, I plan to observe the severity of the changes in capsule size and morphology with the scans I get day after day.

The Growth of Wings and Experiences

Butterflies are something that society has deemed beautiful, and we see countless different species all around the world, all with their own shapes, sizes, and colors. However, not everyone stops to think about how butterflies have come to have such diversity. Many researchers have taken on the task of looking into this question. I am very lucky to be working alongside some of these people.

This summer I am working in Dr. Nijhout’s lab, of which is researching growth in different insect species, meticulously dissecting a lot of caterpillars, albeit with many errors as of now. My objective is to remove the wing that is developing inside of the specimen, to dye it, and to prepare it on a microscope slide so that we can observe the pattern of mitosis occurring throughout the wing disc. It is interesting to see the wing discs at different developmental stages coming from a batch that is the same age. I can remove a disc from one caterpillar that has a beautiful set of veins that have grown in a couple of days. Then I can dissect a different caterpillar from the same container and see that the veins haven’t grown much at all within the same period of time.

When we look at these discs under the microscope, a large mass of nuclei come into focus (with the help of the Hoechst dye). Our job is to take note of the abundance and location of the cells currently going through mitosis. Being that I’m a beginner, it is still quite difficult for me to differentiate between two lumps of nuclei and anaphase, but I am determined to improve with all of Dr. Nijhout’s tips and advice.