End-of-semester CoDE lab update

24 May

A lot is happening in the CoDE lab! Here are some updates on what everyone has been up to this spring and what we are planning for the summer!

Marion Hartl

This semester, Marion spent seven weeks in Tel Aviv to work in the lab of our collaborator Adi Stern on improving accuracy of sequencing methods for HIV patient samples. She very much enjoyed being in a country where being a vegetarian is the norm rather than the exception.

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Melissa Luk

Melissa is graduating this semester with a Major in Cell and Molecular Biology and a Minor in Chemistry. She is very excited to move to UC Davis next semester to start a Master’s Degree in Forensic Science concentrating on DNA track. She enjoys spending time with her nephew, Gabriel.

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Farheen Ghiasuddin

Farheen is graduating this spring with honors as a Physiology Major and a Chemistry Minor. She is planning to take her MCAT soon and then apply for med school in New York. This semester Farheen enjoyed watching The Flash!

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Dwayne Evans

Dwayne presented a poster about his graduate research at the CoSE Showcase. He made a lot of progress with his R coding skills this semester. He is preparing to teach a hiphop class soon.

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Patricia Kabeja

Patricia is graduating this spring with honors as a Physiology Major and a Chemistry Minor. She is planning to take her MCAT soon and then apply for med school on the East Coast. This summer Patricia is going on a medical mission in Jamaica. Patricia’s favorite character in Game of Thrones is Khaleesi.

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Julia Pyko

Julia spent most of this semester interviewing at various medical schools across the country. She received many offers but has not yet selected where she will spend the next 4 years. Her current interests are neurology and OB/GYN. She is getting married this summer and is excited to have all her dogs under one roof again!

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Olivia Pham

Olivia will start a Master’s in the fall (in the CoDE lab!) and she got accepted in the prestigious RISE program. Olivia presented a poster at the CoSE Showcase on the work she did as part of the Microbial Genomics class this semester. Olivia plans to learn to play the drums this summer.

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Kadie Williams

Kadie presented her research at the CoSE Showcase, and won 4th place in the Graduate Life Science category! Congrats Kadie!! She is the co-founder and president of the Biology Student Council.  Currently enjoying her time working on her prospectus and research.

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Dasha Fedorova

Dasha is the president of the MEDLIFE chapter at San Francisco State. She has planned a trip, along with her chapter, to go volunteer in Lima, Peru in June. On this trip, she will be setting up health clinics for low-income communities, as well as helping with various developmental projects. She is graduating Fall 2016, and will be taking the MCAT and applying to medical school shortly after.

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Sidra Tufon

Sidra is graduating this summer as a Physiology Major and a Chemistry Minor. This is her last year of having the title of a fundraising officer for SFSU’s MEDLIFE chapter. She is planning to take her MCAT next April and then applying to med schools for the next cycle. She will also work as a medical assistant while gaining clinical exposure in medical offices this fall. This summer she plans travel to Cabo and Miami with her friends and family as a graduation treat.

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Austin Lim

Austin left the lab early during the spring semester because he found a full time job in a microbiology lab! Congrats Austin!

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PINC! New CS program for Bio majors at SFSU

20 Apr

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The Biology and Computer Science departments at SF State are excited to announce a new program: Promoting Inclusivity in Computing (PINC) with the goal of attracting and supporting more Biology students to Computer Science.

A few faculty members from the Biology department have joined forces with the Computer Science department to design a program that lowers the barriers that Biology students experience in learning computer science skills. This program will expose students to basic computing topics such as web design, mobile app development, data structures, and algorithms. All classes in the PINC program are new and especially designed for biologists.

In the PINC program, biology majors will complete 15 units of computer science course work (5 courses spread over 4 semesters) that will allow the students to earn an “Emphasis in Computer Science”.

For more information about PINC, see pincsfsu.com !

The CoDE Lab presents a summer coding program 2016

5 Apr

The CoDE Lab is very excited to announce a summer coding program that aims to promote more opportunities for undergraduate students to participate in ongoing research!

We have designed a free two-month program that will expose undergraduates not only to research in a lab but also to learn the basics of coding, reading scientific journal articles, and participate in lab meetings. The main goal is for students to learn new skills in the coding language R and be able to apply computational analysis to biological problems.

Program Details

This program will begin June 7, 2016 and run through August 4, 2016.

Our weekly meetings will consist of coding with learning programs such as Udacity, Code Academy, and worksheets provided by the facilitators, reading journal articles related to drug resistance and other topics of research students may be interested in, and lab meetings. Also, we are hoping to go on field trips to various places where coding in biology is applicable!

Each week will look roughy like this:

Course Outline

Who is behind this summer program?

There is four of us organizing the program. We are here to guide and mentor students. Please contact us (phamorrific@gmail.com) if you have any questions. We’d love to hear from you.

Olivia Pham (graduate student in the CoDE lab)

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Dwayne Evans (graduate student in the CoDE lab)

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Kadie Williams (graduate student in the CoDE lab)

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Marion Hartl (Post-doc in the CoDE lab)

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Who is this program for?

This program is for SF State Undergraduates in biology, whom are interested in learning about computational biology, HIV, evolution and/or drug resistance.

Previous experience with programming is not required.

The only requirement for this program is enthusiasm and willingness to work hard. Also, being nice is a plus…! However, we do ask that students who are interested be able to commit at least 6 hours/week during the days that we meet.

If you are not a biology student at SF State but are interested, please contact us and we’ll see what we can do.

How much does the summer program cost?

This program is free for students, there is no fee to apply!

When and where will this summer program be held?

The program will be held in the CoDE Lab at SF State Hensil Hall 520. This program will begin June 7, 2016 and run through August 4, 2016

How to apply?

The deadline to apply is May 6th, 2016.

Please fill out the application at: http://goo.gl/forms/7vGrWC4Mtc

 

eLife paper and video on how HIV treatments affect selective sweeps

15 Feb

Very happy to announce that we have a new paper out and an accompanying video! The paper is about how effective treatments lead to (few) hard selective sweeps and bad treatments lead to soft selective sweeps.

The paper can be found here on the eLife website, but I suggest starting with the video that Alison Feder made.

 

Paper details

Title: More effective drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1.

Authors: Alison F Feder, Soo-Yon Rhee, Susan P Holmes, Robert W Shafer, Dmitri A Petrov, Pleuni S Pennings

DOI: http://dx.doi.org/10.7554/eLife.10670

Abstract: In the early days of HIV treatment, drug resistance occurred rapidly and predictably in all patients, but under modern treatments, resistance arises slowly, if at all. The probability of resistance should be controlled by the rate of generation of resistance mutations. If many adaptive mutations arise simultaneously, then adaptation proceeds by soft selective sweeps in which multiple adaptive mutations spread concomitantly, but if adaptive mutations occur rarely in the population, then a single adaptive mutation should spread alone in a hard selective sweep. Here, we use 6717 HIV-1 consensus sequences from patients treated with first-line therapies between 1989 and 2013 to confirm that the transition from fast to slow evolution of drug resistance was indeed accompanied with the expected transition from soft to hard selective sweeps. This suggests more generally that evolution proceeds via hard sweeps if resistance is unlikely and via soft sweeps if it is likely.

 

New paper, new videos!

31 Dec

With Ben Wilson, Nandita Garud, Alison Feder and Zoe Assaf, I wrote a review paper about population genetics and drug resistance. It was a lot of fun to write this paper and I feel like I learned a lot during the process.

We wrote about drug resistance in influenza, malaria, TB, MRSA and HIV. It turns out that each of these case studies have something unique to teach us about evolution.

The paper is now out in Molecular Ecology. You can also download it here: 2015Wilson_et_al-Molecular_Ecology.

We made five short movies about the paper. Have a look at the one you are most interested in!

Nandita Garud on using genome scans to find resistance loci in malaria

MolEcolNandita from Pleuni Pennings on Vimeo.

Ben Wilson on the role of epistasis in resistance in Influenza

BenMolEcol from Pleuni Pennings on Vimeo.

Pleuni Pennings on standing genetic variation in HIV

MolEcol from Pleuni Pennings on Vimeo.

Alison Feder on clonal interference in TB

MolEcolAlison from Pleuni Pennings on Vimeo.

Zoe Assaf on the origins of the SCCmec element that causes methicillin resistance

MolEcolZoe from Pleuni Pennings on Vimeo.

We have a name: The CoDE Lab

7 Dec

After several brainstorming meetings, we decided on a new name: The CoDE Lab.

CoDE stands for Coding to understand Disease Evolution.

I am very happy with the new name!

CoDELabNov2015

The SFSU CoDE Lab in November of 2015. Kristof Theyss, Dasha Fedorova, Sidra Tufon, Patricia Kabeja, Farheen Ghiasuddin, Pleuni Pennings, Melissa Luk, Marton Hartl, Julia Pyko, Olivia Pham, Austin Lim and Dwayne Evans. Not in the picture: Kadie Williams. 

Selective sweeps in 24 years of HIV sequence data

9 Sep

Together with several collaborators at Stanford, I published a paper on the BioRxiv on selective sweeps in HIV. We find that when treatments didn’t work well (think AZT in the 1980s), sweeps were very soft, but with better treatments sweeps are getting “harder.” The first author on the paper, Alison Feder, has done most of the work on this paper including making all the figures (and they are cool!).

Alison F Feder, Soo-Yon Rhee, Robert W Shafer, Dmitri A Petrov, Pleuni S Pennings. 2015. More efficacious drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1. BioRxiv, doi:http://dx.doi.org/10.1101/024109

Abstract

In the early days of HIV treatment, drug resistance occurred rapidly and predictably in all patients, but under modern treatments, resistance arises slowly, if at all. The probability of resistance should be controlled by the rate of generation of resistant mutations. If many adaptive mutations arise simultaneously, then adaptation proceeds by soft selective sweeps in which multiple adaptive mutations spread concomitantly, but if adaptive mutations occur rarely in the population, then a single adaptive mutation should spread alone in a hard selective sweep. Here we use 6,717 HIV-1 consensus sequences from patients treated with first-line therapies between 1989 and 2013 to confirm that the transition from fast to slow evolution of drug resistance was indeed accompanied with the expected transition from soft to hard selective sweeps. This suggests more generally that evolution proceeds via hard sweeps if resistance is unlikely and via soft sweeps if it is likely.

Figure 3

Figure 3: Drug resistance mutations are correlated with diversity reduction differently in different types of treatments. Treatment efficacy from literature review (% of patients with virologic suppression after 48 weeks) showed positive correspondence with clinical recommendation among RTI regimens (A) and PI+RTI regimens (B). DRM SE lower among the more efficacious and clinically recommended treatments among RTI treatments (C) and RTI+PI treatments (D). Mixed effect model shows significantly different slopes for NNRTI treatments versus NRTI treatments (E) and PI/r treatments versus PI treatments (F). Each line in (EF) represents the fitted decay in diversity with each DRM for a different treatment from the full mixed effects model and p-value labeling indicates the difference between the plotted full model and the null not fitting slopes separately for treatment groups.

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