Notebook HEARTBEAT

Welcome to the notebook of the HEARTBEAT (Heidelberg Artificial Transcription Factor Binding Sites Assembly and Engineering Tool) project. This notebook comprises the work on three sublanes: HEARTBEAT database (DB), HEARTBEAT graphical user interface (GUI) and HEARTBEAT fuzzy modeling (FN) as well as some additional work on logo as well as wiki design. Have fun!

Contents

• July

• August

• September

• October

July

7-27-2009

• Meeting with Oliver Pelz
  • Discuss general ideas of our Database Structure and Content
  • An introduction into PromoterSweep (LINK). PromoterSweep screens a given sequence for conserved regions giving us consensus sequences and moreover screens them for TFBS by using database search (TRANSFAC, Jasper) (LINK)
  • Our new database should contain following informations: promoter sequence, TFs, TFBS, position of TFBS, number of binding TFBS, "host organism"
  • We decide to choose MySQL as a appropiate language solving this challenge which allows us also a graphical representation of the database on the web later.
  • GUI on wiki: which language? php? javascript?
  • Problems: access to PromoterSweep (Husar Bioinformatics Group, DKFZ), choice of Promoter Database (DoOP, UCSC, EnsEMBL) (LINK)

• aim: create database until end of August

[TOP]

AUGUST

8-3-2009

• First contact with MySQL
• Start making an overview of other team's projects
• Configuring our Virtual Server

8-4-2009

• Official Team Meeting (LINK) @ BQ seminar room 43: preparaing presentation & writing meeting report
• Start installing developing environment on our internal server
  • GNOME
  • Mediawiki

8-5-2009

• Meeting with Tobias Bauer & Anna-Lena Kranz (Theoretical Bioinformatics, DKFZ) @ TP3, DKFZ
  • Integrating ideas of PromoterSweep, Transfac as well as DoOP/CisRED
  • select "interesting" TFs (e.g. HIF, NFkB, c-myc, p53) for Wetlab
  • select "interesting" pathways (e.g. cell cycle, inflammation, metabolism etc)
  • future experimental validation: ChIP-on-Chip
    • for this we need a TFBS-free sequence
  • idea: plot histogram of TFBS relative to TSS
    • problem: choice of sequence: upstream only? inculde downstream?
  • new programming language: R and perl
  • next meeting: Friday after team meeting

• Meeting with Karl-Heinz Glatting (HUSAR, DKFZ) @ TP3, DKFZ
  • An introduction into PromoterSweep
  • Structure and analysis principles of PromoterSweep
  • Output is stored in an XML file. This means we have to parse the xml code.
  • Oliver Pelz will give help for us in programming

• Protocol of the meeting can be downloaded from here.

• Start working with MySQL
• request UNIX/HUSAR/HPC access at DKFZ (Nao)
• first contact with several databases: EmsEMBL, Compara, cisRED, DoOP, TiProD, contra (LINKS)

8-6-2009

• Meeting with Oliver Pelz
  • defining workflow with PromoterSweep, Matrix Profile Search and introduction into different Motif Discovery Algorithms

• installation of NX server for access onto internal server from Windows
• configure developing environment (printing from Linux, configure Mediawiki)
• defining basic concept of database construction
  • we select annotated promoter sequences in DoOP
  • we make a selection of pathway of interest using KEGG
  • narrow down number of target promoter sequences <10000.

8-7-2009

• Official Team Meeting on Scheduling
• Meeting with Anna-Lena and Tobias
  • Introduction into R
  • Tobias will give us access to their computing cluster (Group Roland Eils)
  • Promoter Selection: DoOP, EnsEMBL, or UCSC?

• HUSAR account arrived
• installation of R, R editor and perl editor
• further configuration of our internal server / mediawiki

[TOP]

8-10-2009

• first contact with R and perl
• playing around with R and perl
• playing around with R library: Biobase
• check working on DKFZ cluster

8-11-2009

• defining programming languages: perl, R, MySQL
• retrieving first Promotersweep output files

• Meeting with Marti
  • ideas for modeling
    • we will have at least three colors which overlap in their spectra.
    • a very nice approach will be Fuzzy Logic Modeling.
    • idea 1: error checking of affinity: compare expectation to experimental results and figure out where the error is hiding
    • idea 2: create&visualize fancy and fuzzy data from in silico simulation
  • combine: promoter, output and graphic representation (GRAFIK!)
  • next meeting with Marti: end of next week.

• extract NCBI Entrez Gene IDs with R and perl
• MAC adresses registered for bioquant network

8-12-2009

• configure perl working environment
• study structure of DoOP database
• download DoOP and load DoOP database into MySQL

8-13-2009

• trying out some DoOP queries
• download fasta sequences from UCSC gene browser (LINK)
• mapping of NCBI Entrez Gene IDs with RefSeq IDs
• configure perl working environment on Windows XP
• contact Endre Sebestyen concerning the perl module Bio-DoOP-DoOP (LINK)

8-14-2009

• start PromoterSweep Analysis over Weekend

[TOP]

8-18-2009

Tim, Stephen, ab hier müsst ihr eure Sachen selber eintragen!

• study outputfile of PromoterSweep. check out general structure and pick up useful information.
• result is grouped in: General Info, Best Genomic Mapping, Promoter DB Search Result, Graphical Overview, Combined Binding Sites, TSS and Exon Info, Profile Matrices and Generated Output Files.
• upon selection, sections of interest will be collected and made ready for entry into MySQL DB
• discuss table structure of our database

• How should our database be called? - Brainstorming -
  • SHOULD contain: iGEM, Transcription Factor, Binding Site, Promoter, synthetic biology, Heidelberg
  • MAY contain: position, heartbeat, prediction, assembly, eukaryotes
  • and still more keywords to come

8-19-2009

• parse Promotersweep xml file into tab-separated text file (PERL CODE?)
  • the text file should contain: RefSeq ID, TF name, TFBS position, TF motif sequence, TFBS Quality, TSS, Entrez ID, EnsEMBL ID, further gene description.
  • this provided us with several programming problems concerning working with multiple arrays, hashes and their combinations (arrays of hashes, hashes of hashes, etc.) thus
• studying structure and basic concepts of hash & key

8-20-2009

• pre-decision for our table-structure
  • Table: Main_Info
    • RefSeq ID, TF, TF motif start & end position, TFBS motif score, TFBS quality, TSS database info
  • Table: Gene_Info
    • Ensembl_ID, Gene Symbol, Gene Description.
  • we go for the RefSeq ID to be the key connecting these two tables.

8-21-2009

• update script for parsing the Promotersweep output files due to unexpected errors
• we forgot to include "weak" as a category for the TFBS quality - added!
• PromoterSweep result contains information about TSS derived from different promoter databases. On which should we rely, if they differ from each other?
  • We set our highest priority to DoOP database since they show a good accordance within the RefseqID results when compared to other databases (e.g. DBTSS).

• order [http://www.mathworks.com/| Matlab] iGEM licence

• search for a tool to use MySQL in R programming environment
• wiki: write an short article about the German Cancer Research Center (DKFZ)

• Meeting with Anna-Lena: once we established our database... then
  • two strategies:
    • manually select interesting transcription factors and analyse them using database queries
    • plot histograms of TFBS occurance within the target promoter sequence (TSS - 1000bp upstream) for each TF and make systematic analysis
  • we go for both!
  • idea for the future: we can analyze combinatorial appearance of distinct TF pairs

• We have a name for our database - we call it -

- wait for it -

HEARTBEAT database (Heidelberg Artificial Transcription Factor Binding Site Engineering and Assembly Tool)


[TOP]

8-24-2009

• Meeting with Marti: defining output modeling strategies
  • "exclusive promoters"
    • a model for predicting the behaviour of activation of one, two, three... promoters at the same time.
    • the potential of this model lies in the possibility to model single as well as many pathways in combination and even check for synergistic effects
    • modeling logic: quantitative ODE VS. quantitative & qualitative fuzzy logic
  • "error checking"
    • what to capture/measure: affinity of transcription factor binding to DNA
      • calculate score / reliabilty
      • phenotypic measurement
    • if we have time in the end: model/experiment optimization by wetlab-drylab-rounds (GRAFIK)
    • if we do not have much time: figure out where is catch
  • modeling layers & final visualization
    • (i) capture affinity - (ii) model gene expression - (iii) pathway activity - (iv) fancy visualization (Mathworks Simulink?)
    • plot: time course, dynamic affinity
    • keep in mind the possible high amount of False Positives using promoter search/analysis

8-25-2009

• official Team Meeting also with Mr. Kai Ludwig (LANGE + PFLANZ) as guest for Logo / Title Claim discussion

• so far we have 1753 promoter sequences analyzed by PromoterSweep!

• Meeting with Daniela (Nao): Cell Profiler for capturing biological images & data analysis based on MATLAB

• working with R module RMySQL (LINK) for using the pipeline between R and MySQL
• create a list of useful RMySQL commands

8-26-2009

• Workflow for plotting histogram - workflow (SOURCE CODE/S?)
  • make MySQL query using R
  • make list of TFs, avoid duplicates using perl
  • pick up each TF (perl/R) and plot histogram (R)

• create MySQL command list including combinatorial queries

8-27-2009

• check HEARTBEAT DB for duplicate entries
• how should we plot the histogram?
  • (a) histogram - how "wide" should be each bin? 100bp? 50bp? 20bp?
  • (b) plot probability density
• study Transfac PWM (position weight matrices) for
  • difference in consensus sequences (also ask Anna-Lena)
  • different PWM types (vertebrates, plant, insect, fungi, bacteria, nematodes...)
  • positive control: when histograms are generated and plotted, check distribution of Sp1 (LINK)

• so far we have 3640 promoter sequences "sweeped"!

8-28-2009

BBBing of Insertsequences2.0

• Restrictiondigest of flourophores and localisationsequences with SpeI and NheI (1 h, Buffer 2, BSA)
• Restrictiondigest of p49 with SpeI and NheI (1 h, Buffer 2, BSA) and SAP (30 min), purification
• Nanodrop of digest shows no DNA inside of the samples -- purification was maybe unsuccessful

8-29-2009

BBBing of Insertsequences2.1

• Restrictiondigest of flourophores and localisationsequences with SpeI and NheI (1 h, Buffer 2, BSA)
• Restrictiondigest of p49 with SpeI and NheI (1 h, Buffer 2, BSA) and SAP (30 min), purification

8-31-2009

BBBing of Insertsequences2.1 (part 2)

• Ligation of Insertsequences with restricted p49
• Transformation
• Outplating -> Wrong resistance