Influenza
The Blame GameThe greatly feared pandemic flu virus has finally broken out. Millions are sick and thousands have already died. It is almost impossible for the Centers for Disease Control (CDC) to keep track of the new cases reported each day. Contrary to everyone's expectations, the first reported cases appeared in San Francisco and not in Asia or Eastern Europe. From an anonymous source the New York Times is reporting that there was mishandling of the recently reconstituted and extremely dangerous 1918 influenza virus at several labs. Apparently, there was unauthorized shipping of the virus to a Biosafety Level 3 (BSL-3) lab at UC San Francisco and it …
The Blame Gameappears that the package might have been damaged en route to the lab or potentially mishandled onsite at UCSF. In immediate reaction to the newspaper's report all related parties at UCSF have been arrested for the illegal dissemination of a biological agent to the public. Several of the arrested parties are researchers without US citizenship (but with appropriate visas) and some members of congress are calling for immediate deportation or even reclassification of their status to 'Enemy Combatants' and trying them as terrorists. In other related news, the virus strain from San Francisco has been fully sequenced and, just today, released to the public.
PBS video
http://www.pbs.org/wgbh/nova/body/1918-flu.html
Influenza Virus (flu)Small genome—8 RNA molecules
Antigenic glycoproteins
16 Hemagglutinins:Attachement to host
9 Neuraminidases: Passage through mucin, budding
- E.g., H1N1
Influenza A, B, and C
A: the one that can cause pandemics, broad host range (humans, birds, swine, horses…)
B: infects only seals and humans, ~ 1/3 of all influenza cases in US
C: infects humans and swine, causes only mild infections
Influenza Virus (flu)Sequencing
Reverse Transcriptase
DNASequencing
Genomic Nucleotide Sequence
Influenza Pandemics
1918 Flu Killed from 50-100 Mil. people worldwide Considered to be one of the most deadly pandemics Killed many of the young and healthy Influenza A, Type H1N1 Thought to have derived from Avian Influenza Recently reconstituted from recovered human samples Considerable ethical debate
Avian Influenza
Fear of pandemic High mortality rate (including young and healthy) Current concern is Influenza A, Type H5N1 Limited human-human transmission (2 cases as of
2009) in avian flu
Confirmed cases
Swine virus, the fear of viral reassortment
HHMI animation
Post-pandemic stage of swine flu
Antiviral drugs
Amantadine + Rimantadine inhibit one of the matrix proteins and thus passage into the cytosol. By 2008-2009 season, virtually all H3N2 were resistant. .
Kimball’s Biology Pages
Antiviral drugs
Relenza and Tamiflublock neraminidase and thus inhibit the attachment of virions. By 2008-2009, all H1N1 strains circulating in the US were resistant.
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Kimball’s Biology Pages
What is Bioinformatics?
Intersection of Biology and Computers Broad field
Often means different things to different people
Personal Definition: The utilization of computation for biological
investigation and discovery—the process by which you unlock the biological world through the use of computers.
What does one do in Bioinformatics?
(a small sample)
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Our Lab: Understanding Protein (Enzyme) Function
What does one do in Bioinformatics?
(a small sample) Discover new drug targets—computational docking
Atreya, C. E. et al. J. Biol. Chem. 2003;278:14092-14100Shoichet, B. K. Nature. 2004;432:862-865
What does one do in Bioinformatics?
(a small sample) Systems Biology
sbw.kgi.edu/ www.sbi.uni-rostock.de/ research.html
This lab: Nucleotide & Protein Informatics
Sequence analysis Finding similar sequences Multiple sequence alignment Phylogenetic analysis
SequenceStructureFunction
Process of Evolution
Sequences change due to Mutation Insertion Deletion
Use Evolutionary Principles to Analyze Sequences
If sequence A and sequence B are similar A and B evolutionarily related
If sequence A, B and C are all similar but A and B are more similar than A and C and B and C. A and B are more closely evolutionarily related to each
other than to C
Extremely Powerful Idea
1. Start with unknown sequence
2. Find what the unknown is similar to
3. Use information about the known to make predictions about the unknown
How do you know when sequences are similar?
Align two sequences together and score their similarity
TASSWSYIVE
TATSFSYLVG
Use substitution matrices to score the alignment
Substitution Matrices Give a Score for Each Mutation
Many different matrices available Blosum matrices standard in the field
Blosum 62 Scoring matrix
http://www.carverlab.org/images/
Scoring: Add up the positional Scores
Score of 30
TASSWSYIVE
TATSFSYLVG
TASSWSYIVE
TATSFSYLVG
Score of 1
Additional issues…
Gaps (insertions/deletions) Have scoring penalties for opening and continuing a
gap
TASSWSYIVE TASSWSYIVE
TATSFLVG TATSF--LVG
How do we find similar sequences?
Start at the National Center for Biotechnology Information http://www.ncbi.nlm.nih.gov/
How do we find similar sequences?
Nucleotide Sequence Databases
How do we find similar sequences?
Protein Sequence Databases
How do we find similar sequences?
Similarity Search: BLAST Basic Local Alignment Search Tool
BLAST is very quick but … Only local alignments Alignments aren’t great Only pair-wise alignments
Want better alignments … Multiple alignment
Multiple sequences Better signal to noise
More Sequences = Better alignment More accurate reflection of evolution
ClustalW Commonly used Easy to use
Visualize the Multiple Alignment
Use the Alignment to Calculate Evolutionary Distances See ‘how close’ sequences are to each other Best way to tell what is ‘most similar’ Can calculate simple tree from clustalW
Taubenberger et al., Nature: 437, 889-893, 2005
Caveats!
In reality Sequences (even parts of sequences) can evolve at
different rates Don’t have a good understanding of sequence and
function High sequence identity does not always mean the same
function Getting good alignments and good trees can be very
hard
Bioinformatics: Sequence Analysis
1. Start with unknown sequence
2. Find similar sequences
3. Create alignment
4. Create phylogenetic tree
5. Use information about knowns to make predictions about unknown
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