4/26/17

Today we presented our projects to each other and touched up our presentations. Yesterday our group gathered to complete the powerpoint and compile the data gathered using Rho – independent transcription terminase prediction software. This completed our project and provided a form of verification that indicated that promoters were present within the operon.

The next step in this process is to present at the CURES In Bio symposium!

Final consensus sequence data.

Operon identification.

Posted by: Joshua Baker

2-20-17

Today we reviewed annotations for Caterpillar taking care to ensure that the annotations were of the quality demanded of the review board.

2-22-17

Today the entire Caterpillar group gathered together to compile the FASTA file after everyone had completed their individual annotations.

2-27-17

Today Alec and I began to compile the cover sheet. We worked to add any unusual calls to the sheet and talk to members of our team.

3-1-17

Today we had to edit the cover sheet due to some extra comments that were not needed. After we reviewed the sheet with Ashely and then submitted it alongside the other files in a box folder.

3-13-17

Today we picked groups and determined our topics for the posters for the symposium.

3-16-17

Today my group and I worked to develop the poster over the wet lab and bioinformatic lab information.

3-20-17

Today we continued to finish the poster.

3-22-17

Today all the class gathered to present the posters to each other and vote on the poster we wanted to present.

3-27-17

Today was a day were the entire class practiced presenting for the Scholars Week presentation.

3-29-17

Today the entire class presented at Scholars Week. Various groups presented their individual posters to the professors and Baylor students.

4-3-17

Today the class worked to finalize the posters for the local SEA-PHAGE conference.

4-5-17

Today the entire class presented these new posters and shared their opinions with each other.

Posted By: Joshua Baker

04/24/17

One of the biggest problems in phage therapy has been in the approval process. Describe the trouble surrounding FDA approval and recommend some suggestions to improve the process of phage therapy approval.

Bacteriophage therapy is a rather new form of treatment in the United States and is viewed with a high degree of skepticism – a view that seemingly managed to make its way into the FDA approval process. On June 10, 2001 Sulakvelidze meet with Marissa Miller and Brown in a conference call with Washington. “Because bacteriophage therapy was new to the FDA, the government had convened regulators and experts from many different divisions. There were experts from the FDA’s Center for Biologics Review, toxicology experts, microbiologists, and regulatory affairs specialists from the National Institutes of Health.” These individuals are exceptionally knowledgeable, but in their pursuit for perfection I believe that they may serve as a hinderance. Firstly, it is important to consult and verify that drugs will be successful; however, with any form of treatment there may always be some form of risk. The FDA’s request that they determine the mutation rate of these phages seemed unnecessary and I believe is the inherit result of the skepticism mentioned above, phages aren’t widespread throughout the US as are antibiotics and can be seen as threatening. This resistance ultimately forced Sulakvelidze to shelf the project for when his NIAID budget was revoked he simply, “did not have the funding to do it.” Granted it is the duty of the FDA to protect the general populace, but I believe valuable information can be learned from witnessing the results of treatment in other nations will fewer regulations. If it has been successful there then I believe that in order for the US to stay competitive it must lower its initial standards to a place that will empower development and not stifle it.

Furthermore the FDA approval process is a rather long and tedious one. If the, “process of drug development and approval costs an average of $800 million,” then many small companies and individual ideas have no dreams of achieving success. Additionally, the process takes a total of, “10 years,” and in that time needs can change. The lengthy process and almost unaffordable processing costs makes the FDA approval process a major obstacle to any form of development. Enterprise and entrepreneurship can not grow under the stringent rules sit forth by the FDA approval process nor can many companies stay afloat throughout the entire time the process takes to run to completion. As a result I believe that the FDA approval process should be rethought of in a way that it functions as a business and prize efficiency. Too much focus on regulation can make development near impossible and I believe that in order for drug manufacturing to succeed the FDA must embrace the trail aspect of medicine and understand somethings will not be known yet take care to verify its safety. Such a system will still protect the American populace, but won’t completely hinder development.

04/24/2017

Today we finished compiling the consensus sequences in the -10 and -35 region and evaluated their relation to the AN phage consensus sequence as well as the E. coli consensus sequence. Further we completed the Rho – independent transcription terminator prediction to verify operon placement. Figures can be identified below:

Next class we intend to complete the powerpoint and presentation materials.

Furthermore here is the completed abstract:

Arthrobacteriophage Promoter Prediction Within The AQ Cluster

Haley Everroad, Joshua Baker, Madison Powell

Department of Biology, Baylor University, Waco, Texas, USA

Abstract

Despite recent interest in Arthrobacteriophage, little is known about their promoter sequences. The objective of this study was to predict and identify potential promoters between genes 10 & 11 and genes 83 & 84 of phages in the AQ cluster. The forward and reverse strands diverge at this point allowing us to conclude that promoters are present. Due to high nucleotide similarity between the AQ phages, our group used the Sigma 70 promoter prediction software within DNA Master to identify potential promoters and develop a consensus sequence. Sigma 70 uses the E. coli consensus sequence -35(TTGACA)_17 +/- 1 bp_-10(TATAAT) and a statistical algorithm to score potential promoters on an arithmetic scale – with the highest score equaling a value of one.1 Data was then compiled and averaged to determine a potential consensus sequence for AQ phages. Promoter presence was verified with the application of termination prediction programs to identify entire operons. Thereafter, the AQ consensus sequence was compared to the E. coli consensus sequence and a potential consensus sequence developed independent to this project within the AN cluster. Ultimately, this is a initial venture into Arthrobacteriophage promoter prediction that has the potential to lead to a better understanding of bacteriophage and bacterial promoters in general.

Resources

1. Harley, C B, and R P Reynolds. “Analysis of E. Coli Promoter Sequences.” Nucleic Acids Research 15.5 (1987): 2343–2361. Print.

4/19/17

The Pham – Haley, Josh and Madison

Today we focused on gathering promoter data from DNA master using the Sigma 70 promoter prediction software. The top 100 scores were printed from the five before mentioned phages. Thereafter data was compiled in an excel worksheet and promoters were selected if they fell between the gaps  . Hopefully, we will then be able to use this data to determine a consensus sequence and compare it to the AN consensus sequence. Additionally, further tests can be performed pertaining to the presence of tRNA and the placement of a phage in the AQ cluster if time persists.

Segment of Excel worksheet.

4/10/17

The Pham – Haley, Josh and Madison

Today we determined what our project was going to be. The goal was to identify promoters in AQ phages and to compare them to the data gathered by Ashley and Lathan in AN phages as well as E. coli promoters. The phages that would be used in this study in the AQ cluster include Amigo, SorJuana, Gorgeous, Anansi, and Ring. A consensus sequence will be identified using data specifically gathered in the gap between genes 10 and 11. Hopefully this data can be used and compared to predicted promoters in other gaps within the phage and used to identify operons using terminase prediction if possible.

Furthermore, we are interested in determining if promoter sequences are conserved between bacteria. Gammaproteobacteria and Actinobacteria are rather divergent from each other in a phylogenetic tree. Data from this experiment may help to answer that question.

Future work – next class – will focus on the weighting of the -10 and -35 region in order to run sigma 70 promoter predictor in DNA master and equation formulation. Also we should search for articles that identify promoters in Arthrobacteriophage and possibly use that information to assist in this experiment. In addition, fasta files will need to be downloaded and ran in DNA master.

Split trees could be ran to determine how close AN and AQ phages are and to compare their consensus sequences. BRIG analysis. Furthermore, we could determine is the clustering of one of the phages in the AQ cluster is correct.

Eliava and d’Herelle introduced phage therapy in the 1930’s in the USSR. It’s usage varied as time passed, but never faded as it did in the United States. The duo managed to convince individuals that the therapy was effective and phage therapy labs appeared all across the USSR. Physicians began to administer bacteriophages for various infections such as skin, eye, and ear infections. With this strong support and background tradition was altered in the USSR allowing phage therapy treatments to become the norm while the lack of use in the United States resulted in a hostile relationship in favor of more commonplace treatments such as antibiotics.

In the USSR the war effort continued to influence the application of phages. War required battlefield surgeons to employ phage techniques when combating inflections in surgery. This widespread usage of phage therapy continued to spread throughout all of Russian society and created a cultural norm. Interestingly antibiotics were introduced during the war as a result of the Tehran conference and the top western minds were sent to the USSR to brief the Russians on their latest advancements including the usage of antibiotics. With western funding the USSR began to produce these antibiotics, but after the war ended and with it western funding and antibiotic education the usage of antibiotics in Russian medicine faded.

The political fear that came with the rise of the USSR managed to even reach to the scientific field and carried with it Jewish persecution from the Second World War. Lysenkoism grew widespread throughout the Soviet Union and as a result the Hirszfeld Institute had a difficult time beginning due to an incorrect belief that genes don’t actually exist. In addition, the “Doctor Plot” which targeted Jews also hindered Hirszfeld personally. Even after the establishment of the institute in 1954 Hirszfeld passed away the same year resulting in a leadership deficit that was filled by a Stefan Slopek. Finally the institute began to perform its original function. However, had the political turmoil not existed during the time of the institute’s creation it would be interesting to see how the application of phage therapy would have influenced medicine during that influential time period. In comparison the Eliava Institute seemed to flourish during this time and it could be noted that d’Herelle’s belief in Lysenkoism and political connections played a large roll in this contrast.

In 1963 Merril decided to see for himself why phages didn’t have a long span of action and realized that the mice’s bloodstream – which had been injected with phages – would remove these organisms rapidly because these phages had not yet evolved to evade the body system. With the assistance of Carlton and Adhya, Merril began to carry out his experiment. The breeding process for effective phage use in the blood stream was not much unlike other breeding techniques like those used for finding effective phages in combating bacteria. After seven hours in the bloodstream phages that were injected and survived the liver and spleen where then amplified and then reinjected into the mice. After eight trials Argo 1 and 2 had been discovered. These phages could stay in the blood stream for a total of 18 hours which was an impressive feat. Thereafter they were tested against E. coli infections in mice and the scientists encountered stunning success. All the mice treated with the phage survived while none of the untreated mice survived. Also those mice treated with Argo 1 and 2 had a higher rate of survival than those just treated with the wild-type strain of the phage. A massive achievement for phage therapy.

Private enterprise rules in a capitalistic society. In this system people strive to make money and find success in an economy that is just about open to anything unless laws stand in the way. Such is the case in the United States with regard to phage therapy. The FDA’s regulations on phage therapy makes development difficult, yet not impossible. In continuation experiments are going to have to be performed to verify the safety of widescale phage therapy treatment to gain greater FDA approval and favorable regulations. In addition, these tests will help to sway public open much like advertisement did in the USSR. Phage therapy has only recently reemerged in the United States; however, if private enterprise continues to push for practical applications it isn’t unlikely to assume that phage’s may begin to play a more prominent role in American medicine.

Joshua Baker

02/15/17

Today we annotated genes 4-11.

Tools used and/or Methods: DNA Master, PhagesDB BLAST, NCBI BLAST, Starterater, and HHPred.

Results:

Gene 4

Start: 1620bp Stop: 2729bp FWD GAP: 20bp Gap SD Final Value: SD Score: -2.077 (Best score) Z-Value: 3.188 CP: The gene is not covered The gene can’t be extended to cover all – approximently 20 bp left uncovered. SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: endolysin [Arthrobacter phage Gordon] Q:1 S:1 E-Value: 0.0 CDD: PGRP and Cpl-7 domain-containing protein E-Value: 2.2e-13 PhagesDB BLAST: Gordon_4, endolysin Q:1 S:1 E-Value: 1e-164 HHPred: Endolysin, putative lys E-Value: 2.3e-23 LO: Yes ST: Agrees with Starterator F: FS: HHpred, NCBI, PhagesDB Notes: Endolysin; PGRP and Cpl-7 domain-containing protein

Gene 5 POSSIBLE DELETION

Gene 6 POSSIBLE DELETION

Gene 7

Start: 2886bp Stop: 3269bp FWD GAP: 8bp Overlap SD Final Value: SD Score: -2.904 (Best score) Z-Value: 2.767 CP: The gene is not covered The gene can’t be extended to cover all – approximently SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: hypothetical protein GORDON_5 [Arthrobacter phage Gordon] Q:6 S:39 E-Value: 2.0e-50 CDD: No good hit PhagesDB BLAST: Gordon_5, function unknown Q:6 S:39 E-Value: 6e-41 HHPred: No good hit LO: Yes ST: We cannot shorten the gene without losing the best z-score, SD value, and longest open reading frame F: NKF FS: NCBI, PhagesDB Notes:

Gene 8

Start: 3266bp Stop: 3793bp FWD GAP: 4bp Overlap SD Final Value: SD Score: -3.207 (Best score) Z-Value: 3.047 CP: The gene is not covered The gene can’t be extended to cover all – approximently SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: hypothetical protein GORDON_6 Q:18 S:1 E-Value: 2e-74 CDD: No good hit PhagesDB BLAST: Gordon_6, function unknown Q:18 S:1 E-Value: 6e-59 HHPred: No good hit LO: Yes ST: We cannot shorten the gene without losing the best z-score, SD value, and longest open reading frame F: NKF FS: NCBI, PhagesDB Notes:

Gene 9

Start: 3812bp Stop: 5551bp FWD GAP: 18bp Gap SD Final Value: SD Score: -2.137 (Best score) Z-Value: 3.188 CP: The gene is covered SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: terminase large subunit [Arthrobacter phage Gordon] Q:1 S:1 E-Value: CDD: Phage terminase-like protein, large subunit, contains N-terminal HTH domain [Mobilome E-Value: 3.99e-49 PhagesDB BLAST: Gordon_7, terminase, large subunit Q:1 S:1 E-Value: 0.0 HHPred: Terminase, DNA packagin E-Value: 1.1e-27 LO: Yes ST: Agrees with Starterator F: terminase, large subunit FS: NCBI, PhagesDB, HHpred Notes:

Gene 10

Start: 5548bp Stop: 6399bp FWD GAP: 4bp Overlap SD Final Value: SD Score: -2.451 (Best score) Z-Value: 3.043 CP: The gene is covered SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: hypothetical protein CAPNMURICA_8 Q:1 S:1 E-Value: 0.0 CDD: No good hit PhagesDB BLAST: CapnMurica_8, function unknown Q:1 S:1 E-Value: 1e-152 HHPred: No good hit LO: Yes ST: Agrees with Starterator F: NKF FS: NCBI, PhagesDB Notes:

Gene 11

Start: 6396bp Stop: 6977bp FWD GAP: 4bp Overlap SD Final Value: SD Score: -4.241 (Best score) Z-Value: 2.184 CP: The gene is covered SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: hypothetical protein GORDON_9 Q:5 S:4 E-Value: 1e-79 CDD: No good hit PhagesDB BLAST: Niktson_Draft_8, function unknown Q:1 S:1 E-Value: 6e-75 HHPred: No good hit LO: Yes ST: Agrees with Starterator F: NKF FS: NCBI, Phages DB Notes:

Conclusions and Next Steps: Genes 5 and 6 were skipped over so that way we can call a group meeting and determine which one to delete. The reverse gene (5) has a better SD score and Z-value; however, the forward gene has the better start (its an ATG) and is more likely to exist being the fact that its a reverse gene. All BLAST databases don’t offer much light on the subject. Overall the other genes were easily sequenced and did not cause too much trouble. There have been a few cases were the coding potential is not entirely covered, but they are by maybe a gap of 20bp and may to the cause of some underlying genetic mutation or the result of the software. The intention is to continue annotating the genome in the next lab.

Joshua Baker

02/13/17

Today a gene was added (1.2) and two more genes were annotated – 2 and 3.

Tools used and/or Methods: NCBI BLAST, DNA Master, HHPred, Starterater, and PhagesDB BLAST.

Results:

Gene 1.2

Start: 528bp Stop: 680bp FWD GAP: 175bp Gap SD Final Value: SD Score: -4.679 (Best score) Z-Value: 2.009 CP: The gene is not covered We added a gene that was not covered, but satisfied other conditions SCS: Disagrees with Glimmer, Disagrees with GeneMark We inserted a gene in this position because it filled a gap that was too large, and opened the longest reading frame with the best z-score, standard deviation, and had a common start codon NCBI BLAST: No good hit CDD: No good hit PhagesDB BLAST: No good hit HHPred: No good hit LO: Yes ST: We added this gene and no information on Starterator can be identified. F: NKF FS: HHpred, NCBI, PhagesDB Notes: No Starterator data was gathered. Due to the large gap and a good SD and e-value call we decided that this would be the be a decent section to include a new gene. 

Gene 2

Start: 831bp Stop: 1199bp FWD GAP: 150bp SD Score: -2.047 (Best score) Z-Value: 3.194 CP: The gene is covered SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: Hypothetical protein GORDON_1 Q:1 S:1 E-value: 2.2e-13 CDD: No good hit PhagesDB BLAST: Gordon_1, function unknown Q:1 S:1 E-Value: 2.0e-55 HHPred: No good hit LO: Yes ST: Agrees with Starterator F: NKF FS: NCBI, PhagesDB Notes: Although the gap is rather large, with respect to promoters there are not enough nucleotides to form a gene. This is supported by no results from NCBI blast, and Genemark did not indicate any coding potential.

Gene 3

Start: 1189bp Stop: 1599bp FWD GAP: 11bp Overlap SD Final Value: SD Score: -2.159 (Best score) Z-Value: 3.142 CP: The gene is covered SCS: Disagrees with Glimmer, Agrees with GeneMark We chose to agree with GeneMark because it gives the best open reading frame, z-score, and standard deviation NCBI BLAST: HNH endoluclease domain protein [Arthrobacter phage Gordon] Q:3 S:2 E-Value: 1e-89 CDD: No good hit PhagesDB BLAST: Gordon_2, HNH endonuclease domain, 135 Q:3 S:2 E-Value: 2e-72 HHPred: No good hit LO: Yes ST: We enlogated the gene and can not use Starterator as a resutl. F: HNH endonuclease FS: HHpred, NCBI, PhagesDB Notes: We elongated this gene so that we would be completely covered by GeneMark, have the best z-score, standard deviation, and open reading frame

Conclusions and Next Steps: We decided to enter in another gene within the 400 bp gap between gene 1 and gene 2. We decided to enter it in a place that would yield the highest SD value and Z-value (both of which confirmed its existence). We concluded that a gene must be here even though GeneMark did not call for it because of the fact that phage genomes are rather dense and that there is no room for a large amount of spare nucleotide sequences.

Joshua Baker

02/08/17

Today annotations for gene 1 of Caterpillar were completed.

Tools used and/or Methods: DNA Master, Starterator, GeneMark, HHPred, NCBI BLAST, PhagesDB BLAST

Results:

Gene 1

Start: 176bp Stop: 352bp FWD GAP: 175bp Gap SD Final Value: SD Score: -3.085 (Best score) Z-Value: 2.72 CP: The gene is covered SCS: Agrees with Glimmer, Agrees with GeneMark NCBI BLAST: No good hit CDD: No good hit PhagesDB BLAST: No good hit HHPred: No good hit LO: Yes ST: Agrees with Starterator F: NKF FS: HHpred Notes:

GeneMark declared there was coding potential for this gene.

Conclusions and Next Steps: Gene one did not have strong HHPred or BLAST results indicating that if this were to be an actual gene that it has yet to have been discovered in another phage. Nonetheless the SD score, coding potential, and Z-value were all excellent and because of that data we decided that it was best to call this gene despite the lack of confirmation about its existence from BLAST databases. It is out intent to continue to annotate the remaining genes in the next couple of lab periods.