[Bio] / FigWebServices / eggs.cgi Repository:
ViewVC logotype

View of /FigWebServices/eggs.cgi

Parent Directory Parent Directory | Revision Log Revision Log


Revision 1.11 - (download) (annotate)
Fri Jun 10 13:49:16 2011 UTC (8 years, 5 months ago) by parrello
Branch: MAIN
CVS Tags: mgrast_dev_08112011, mgrast_dev_08022011, rast_rel_2014_0912, myrast_rel40, mgrast_version_3_2, mgrast_dev_12152011, rast_rel_2014_0729, mgrast_release_3_1_2, mgrast_release_3_1_1, rast_rel_2011_0928, mgrast_dev_10262011, HEAD
Changes since 1.10: +2 -4 lines
More fixes for Sveta

use warnings;
use strict;

use CGI qw(:standard);

use FIG;
use FIG_Config;
use FIG_CGI;
use UserData;
use FigWebServices::SeedComponents::Framework;
use FigWebServices::WebApplicationComponents qw(table2);

print header();

eval {
    &main();
};

if($@) {
    print start_html();
    print STDERR "EXCEPTION: $@\n";
    print "EXCEPTION: $@\n",end_html();
}

1;

sub main {

    my $fig = new FIG;
    my $cgi = new CGI;

    my $parameters = { fig_object  => $fig,
                       table_style => 'plain',
                       fig_disk    => $FIG_Config::fig_disk . "/",
                       form_target => 'eggs.cgi'
        };

    print FigWebServices::SeedComponents::Framework::get_plain_header($parameters);

    my $genome     = $cgi->param('genome') || '243273.1';
    my $experiment = $cgi->param('experiment') || 'MG_essential_Hutchison_2006';
    my $value      = $cgi->param('value');

    print qq"<style> .box { padding-bottom: 15px; padding-left: 20px; width: 90%; text-align: justify; } h4 { font-size: 16pt; } #table_results { font-size: 11pt; font-family: arial; } </style>
        <script type='text/javascript' src='./Html/layout2.js'></script>
        <link rel='stylesheet' type='text/css' href='./Html/css/seedviewer.css'>";
    
    if (defined($cgi->param('show_result'))) {
        my $result_table = get_result_table($fig, $genome, $experiment, $value);
        print $result_table;
    } elsif (defined($cgi->param('tuta'))) {
        print get_tut_1();
    } elsif (defined($cgi->param('tutb'))) {
        print get_tut_2();
    } else {

        print get_headline();
        
        print get_introduction();
        
        print get_description();

        print get_tutorial();   
        
        print get_overview_table();
        
        print get_overview_table_footnotes();

        print get_references();

        print "<hr/>";
        
        print get_subsystem_explaination();

    }
    
    print "</body></html>";
}

sub get_introduction {
    my $content = "<div class=box>";

    $content .= "SEED maintains a database of microbial gene essentiality data experimentally obtained from published genome-scale gene essentiality screens (listed in <a href='#table1'>Table 1</a>).  Comparative analysis of these data across multiple organisms in a rich genomic, biochemical, and phylogenetic contexts provided by the collection of annotated <a href='#subsystem'>Subsystems</a> greatly facilitates their interpretation and practical applications, such as,  understanding of cellular networks, gene and pathway discovery, identification of novel drug targets, and strain engineering.";
    
    $content .= "</div>";

    return $content;
}

sub get_headline {
    my $content = "<div class='box'>";

    $content .= "<a name=top /><h1>EGGS database: Essential Genes on Genome Scale</h1>";

    $content .= "</div>";

    return $content;
}

sub get_result_table {
    my ($fig, $genome, $experiment, $value) = @_;

    if ($value eq "essential") {
        $value = ["essential", "potential_essential"];
    }
    my @rows;
    my $rdbH = $fig->db_handle;
    my @essentialities = $fig->get_attributes("fig|$genome.%", $experiment, $value);
    my %pegHash = map { $_->[0] => [$_->[2], $_->[6], $_->[4]] } @{$fig->all_features_detailed_fast($genome)};
    for my $essentiality (@essentialities) {
        my ($peg, $experiment, $essential) = @$essentiality;
        my $pegData = $pegHash{$peg};
        if ($pegData) {
            my @subs = $fig->peg_to_subsystems($peg);
            push @rows, [$peg, $pegData->[0], $pegData->[1], $essential, $pegData->[2], \@subs];
        }
    }
    my $columns = ['#', 'peg ID', 'external ID', 'gene name', 'essentiality', 'SEED annotation', 'subsystems'];
    my $data = [];
    my $i = 1;
    foreach my $row (sort { $a->[4] <=> $b->[4] } @rows) {
        my $gname = "";
        if ($row->[1] =~ /^([a-zA-Z]{3}[^,]*)/) {
            $gname = $1;
        }
        my $ext_id = "";
        if ($row->[1] =~ /([^,]+),NP_/) {
            $ext_id = $1;
        }
        push(@$data, [ $i, "<a href=seedviewer.cgi?page=Annotation;feature=". $row->[0] . ">" . $row->[0] . "</a>", $ext_id, $gname, $row->[3], $row->[2], join('<br/>', @{$row->[5]}) ]);
        $i++;
    }
    
    my $table_params = { data              => $data,
                         columns           => $columns,
                         perpage           => 0,
                         sortable          => 1,
                         show_filter       => 1,
                         operands          => { 'gene name'       => '',
                                                'SEED annotation' => '' },
                         id                => "results"
    };
    
    my $content = "<div class='box'><a name=result_table />";

    $content .= &table2($table_params);

    $content .= "</div>";

    return $content;
}

sub get_subsystem_explaination {
    my $content = "";

    $content .= "<div class='box'>";

    $content .= "<a name='subsystem'><h4>Subsystems</h4><a href='#top'>back to top</a>
<p>Subsystems in SEED are developed and maintained by curators aiming to capture the current status of knowledge of specific biological processes (e.g. metabolic pathways or multipeptide complexes) in model species and to project this knowledge to other species via comparative genomics and metabolic reconstruction techniques (<a href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16214803&query_hl=2&itool=pubmed_docsum'>Overbeek et al., 2005</a>). Populated subsystems are spreadsheets connecting relevant functional roles with annotated genes in hundreds of integrated genomes.  Core metabolic subsystems often contain extensive notes and diagrams helping to understand topology and variations in subsystem implementation (functional variants) across a collection of diverse species.  SEED Subsystem collection is available <a href='SubsysEditor.cgi'>here</a>. Examples of about 50 subsystems are available <a href='http://www.theseed.org/SubsystemPaperSupplementalMaterial/index.html'>here</a> and discussed in detail in (<a href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16214803&query_hl=2&itool=pubmed_docsum'>Overbeek et al., 2005</a>).</p>

<p>Subsystem (SS) spreadsheet is used in SEED as a framework for integration of various types of data organized as gene attributes (including essentiality, gene clustering on a chromosome, virulence, microarray data, relevant publications, etc).  Projection of experimentally determined essentiality assertions over a collection of subsystems in SEED opens new opportunities for data evaluation and functional interpretation:</p>
<ul>(i) subsystems-based annotations help establish accurate gene correspondences between genomes, facilitating cross-organism comparison and projection of gene essentiality data.  This approach overcomes many of the problems plaguing the common homology-based projections by exploiting the functional, genomic, and phylogenetic context of each gene, allowing for many-to-many projections and accounting for non-orthologous gene displacements;</ul>
<ul>(ii)  it allows rationalization of essentiality of each gene and each functional module in the context of the organism's metabolism as a whole;</ul>
<ul>(iii)  facilitates detection and reconciliation of inconsistencies in experimental data:  inspection of essentiality assertions of all genes in the same pathway as a group imposes the requirement for internal data-set consistency, and for data correlation with the existing knowledge of a pathway topology, serving as built-in quality control.</ul>
";

    $content .= "</div><br /><br /><br /><br />";

    return $content;
}

sub get_tutorial {
    my $content = "";

    $content .= "<div class='box'>";

    $content .= "<h4>How to use EGGS database</h4>
<p><b>I. Visualization and analysis of essentiality data in <a href='#subsystem'>Subsystem</a> context:</b>
Essentiality data can be visualized in the biochemical and phylogenetic contexts of a Subsystem (SS) spreadsheet. This type of analysis performed across 134 metabolic Subsystems has been published by <a href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16978855&query_hl=2&itool=pubmed_docsum'>Current Opinion in Biotechnology</a>.</p>

<p>To view essentiality assessments of genes in the context of SS spreadsheet click <input type=button value='Subsystem Spreadsheet' onclick='location=\"eggs.cgi?tuta=1\";'></p>

<p><b>II. Essentiality of individual genes can be viewed from a gene/protein (PEG) page.</b> A link <input type=button value='Show' onclick='if (this.value == \"Show\") { this.value = \"Hide\"; } else { this.value = \"Show\"; }'> <b>Attributes</b> is available near the bottom of every PEG page. Activating this link opens a list of various attribute Keys associated with the gene or its protein product (see <a href='http://theseed.uchicago.edu/FIG/Html/Attributes.html'>Help on Attributes</a>), including gene essentiality.  Column 'Key' lists all the experiments (gene essentiality datasets), in which this gene has been scored.  Column 'Value' shows essentiality assessments (contradicting at times) made in each experiment.  Please, note specific environmental conditions and experimental details that might have influenced each essentiality call, outlined in <a href='#table1'>Table 1</a> and specified in the original publication.</p>

<p><b>III. To view a complete list of essential (E) or nonessential (N) genes</b>, as well as all essentiality assignments (E, N, and U) produced in a specific experiment, open <a href='eggs.cgi#table1'>Table 1</a> and click on a number (corresponding to the experiment of interest) that appears in one of the columns: <b>Essentiality assessment: ORFs total, E, N, or U.</b> The resultant output table(s) can be sorted by any of the columns (by clicking on a heading) or searched by typing key words into a search field provided.</p>

";

    $content .= "</div>";

    return $content;
}

sub get_tut_1 {
    my $content = "<div class='box'>

<h4>Visualization and analysis of essentiality data</h4>
<h4>Subsystem Spreadsheet</h4>

<ul>1. Open the Subsystem of interest from the <a href='SubsysEditor.cgi' target=_blank>list of Subsystems</a> in SEED by clicking on a Subsystem name.</ul>
<ul>2.  Limit display to a specific group of organisms and/or roles, if necessary.  We recommend displaying only organisms, for which global gene essentiality data are currently available.  To do so, under the <b>Limit Display</b> tab on a Subsystem page highlight the genome subset <em>SvetaG_Ess-ty_data_available</em> in the <b>UserSets</b> menu box and press the <b>Limit Display</b> button.
</ul>
<ul>3.  In <a href='eggs.cgi#table1'>Table 1</a> identify the name of the Experiment (Attribute) associated with the essentiality data-set of interest</ul>
<ul>4.  Under the <b>Color Spreadsheet</b> tab activate the radio button <b>by attribute</b>, choose the Experiment from a drop-down menu and click the <b>Color Spreadsheet</b> button.</ul>
<ul>5.  Locate the row in the SS spreadsheet corresponding to the organism, for which essentiality data were obtained.  The cells in this row are now colored to show 'essential' or 'non-essential' genes as determined in each study.  Genes, for which no reliable data were obtained appear as 'undetermined'.</ul>
<ul>6.  To display simultaneously essentiality data-sets in the following organisms:  <i>Escherichia coli</i> K12, <i>Bacillus subtilis</i>, <i>Haemophilus influenzae</i>, <i>Helicobacter pylori</i>, <i>Mycobacterium tuberculosis</i>, <i>Mycoplasma genitalium</i>, <i>Pseudomonas aeruginosa</i>, <i>Salmonella typhimurium</i>, <i>Staphylococcus aureus</i>, <i>Streptococcus pneumoniae</i> (one dataset per organism - marked with a red star in <a href='eggs.cgi#table1'>Table 1</a>) - choose the attribute key 'Essential_Gene_Sets_Bacterial' from a drop-down menu and click the <b>Color Spreadsheet</b> button.</ul>

</div>";

    return $content;
}

sub get_tut_2 {
    return "";
}

sub get_description {
    my $content = "";

    $content .= "<div class=box style='padding-bottom: 0px;'>";

    $content .= "<h4>EGGS contents and structure <input type='button' value='show' id=desc_show onclick=\"change_element2('desc');\"><input type='button' value='hide' id=desc_hide class=hideme onclick=\"change_element2('desc');\"></h4>

<span id='desc_content' class='hideme'>
<p>Gene essentiality data in SEED are integrated as gene attribute key-value pairs (see <a href='http://theseed.uchicago.edu/FIG/Html/Attributes.html'>Help on Attributes</a>).  Each attribute Key corresponds to a single experimental data-set generated under uniform genetic and environmental conditions (briefly outlined in <a href='#table1'>Table 1</a>, follow the links to original publications for details).  If two or more independent studies have been published for an organism (e.g., for E. coli, S. aureus, S. pneumoniae), several Attributes are associated with the corresponding genome  in SEED.  Note, that gene essentiality assertions ('Values') obtained for the same gene in different experiments ('Keys') may differ and even contradict each other.  In addition, several derived Keys were generated by merging:</p>
<ul>(i) The two datasets obtained for S. aureus to yield a Key: 'SA_essential_merged'</ul>
<ul>(ii)        The two  datasets obtained for S. pneumoniae:  'SP_essential_merged_Ji_Forsyth'</ul>
<ul>(iii)       Gene essentiality data for 10 microbial species (a single dataset per organism, marked in <a href='eggs.cgi#table1'>Table 1</a>) to yield a combined nonredundunt dataset 'Essential_Gene_Sets_Bacterial'</ul>

<p>To facilitate comparative analysis of gene essentiality data in SEED, the original heterogeneous essentiality assignments have been converted to a unified format: 'essential' (E), 'nonessential' (N), with a default attribute 'undefined' (U) for all other genes.  In several ambiguous cases an authors' notion of 'possibly essential gene' has been retained.</p>

<p>The notion of gene essentiality is meaningful only in the context of specific environmental and genetic conditions it was surveyed under (see <a href='#table1'>Table 1</a>).  The specifics of technology used to generate each dataset influence gene essentiality assessments as well.  The important distinction between the techniques is whether the growth of each mutant occurs clonally or in a mixed population.  Although in both strategies gene 'essentiality' is deduced from the inability of a mutant cell to undergo a certain number of divisions, the passing threshold is much more stringent in mixed populations than in clonal studies. Thus, a mutant with substantially decreased fitness would be quickly selected against under the conditions of competitive outgrowth in planktonic culture, while it might still be capable of forming an isolated colony. In EGGS database E (essential gene) stands for 'essential for survival' for the datasets generated via clonal outgrowth and 'essential for fitness' for datasets generated via populational screens (<a href='#table1'>Table 1</a>).</p>
</span>
";

    $content .= "</div>";

    return $content;
}

sub get_overview_table_footnotes {
    my $content = "";

    $content .= "<div class='box'>";

    $content .= "<a name='footnotes'><b>Footnotes:</b><br/>
The actual numbers of essential and nonessential genes in EGGS database might differ slightly from those published in each original study.  These omissions are due to automatic gene IDs mapping, variances in ORF calling, and other potential mistakes and will be gradually corrected via manual curation.
<ul>1  Termed 'candidate-essential' genes, authors expect about half of these genes to be truly essential based on statistic and bioinformatic analysis</ul>
<ul>2 deduced by comparison of the two gene essentiality datasets obtained independently in the P. aeruginosa strains PA14 [16] and PAO1 [9]</ul>
<ul>3  only partial dataset was obtained</ul>
<ul>4  168 from these have been disclosed</ul>
<ul>5  largely identified experimentally, this list also includes predicted gene essentiality and data compilation from published single-gene essentiality studies</ul>
";

    $content .= "</div>";

    return $content;
}

sub get_overview_table {

    my $content = "<hr /><div class='box'>";

    $content .= qq~
<style>
#simple_table td {
    vertical-align: middle;
    border: 1px solid black;
}

.simple_table {
    border-spacing: 0px;
    border-collapse: collapse;
    font-family: arial;
    font-size: 11pt;
}

.red {
  color: red;
}

.bold {
    font-weight: bold;
    background-color: #688fc5;
    color: #fff;
}
</style>
<a name=table1 /><h4>Table 1. Genome-scale experimentally determined bacterial gene essentiality data-sets available in SEED</h4><a href='#top'>back to top</a><br /><br />
<table class='simple_table' id='simple_table'>
  <tr><td rowspan=2 class='bold' align=center>Organism</td><td rowspan=2 class='bold' align=center>SEED genome ID</td><td rowspan=2 class='bold' align=center>Experiment</td><td colspan=2 class='bold' align=center>Mutagenesis</td><td colspan=2 class='bold' align=center>Mutant outgrowth</td><td colspan=4 class='bold' align=center>Essentiality assesment</td><td rowspan=2 class='bold' align=center>Reference</td></tr>
  <tr><td class='bold' align=center>Strategy</td><td class='bold' align=center>Mutation</td><td class='bold' align=center>Strategy</td><td class='bold' align=center>Environmental conditions</td><td class='bold' align=center>ORFs total</td><td class='bold' title='non-essential' align=center>N</td><td class='bold' title='essential' align=center>E</td><td class='bold' title='undetermined' align=center>U</td></tr>
<tr><td>BS, EC, HI, HP, MG, MT, PA, SA, SP, ST</td><td></td><td>Essential_Gene_Sets_Bacterial</td><td colspan=9>Combined nonredundant dataset, includes global gene essentiality data for 10 bacterial species (a single dataset per organism, labeled with a red star below)</td></tr>
<tr><td>M.genitalium</td><td>243273.1</td><td><span class='red'>*</span>MG_essential_Hutchison_2006</td><td>random</td><td>insertion</td><td>clones</td><td>Rich undefined medium SP4, 37&#176;C, microaerobic growth in 5% CO<sub>2</sub></td><td><a href='eggs.cgi?genome=243273.1&experiment=MG_essential_Hutchison_2006&show_result=1'>482</a></td><td><a href='eggs.cgi?genome=243273.1&experiment=MG_essential_Hutchison_2006&value=nonessential&show_result=1'>100</a></td><td><a href='eggs.cgi?genome=243273.1&experiment=MG_essential_Hutchison_2006&value=essential&show_result=1'>382</a></td><td>0</td><td>[<a href='#ref14'>14</a>]</td></tr>
<tr><td>S. aureus N315</td><td>158879.1</td><td>SA_essential_Ji</td><td>random</td><td>antisense RNA</td><td>clones</td><td>Rich undefined medium TSA,  aerobic growth</td><td><a href='eggs.cgi?genome=158879.1&experiment=SA_essential_Ji&show_result=1'>2,600</a></td><td>n/a</td><td><a href='eggs.cgi?genome=158879.1&experiment=SA_essential_Ji&value=essential&show_result=1'>168</a><a href='#footnotes'><sup>3</sup></a></td><td>n/a</td><td>[<a href='#ref2'>2</a>]</td></tr>
<tr><td>S. aureus N315</td><td>158879.1</td><td>SA_essential_Forsyth</td><td>random</td><td>antisense RNA</td><td>clones</td><td>Rich undefined medium LB+0.2% glucose,  37&#176;C, aerobic growth</td><td><a href='eggs.cgi?genome=158879.1&experiment=SA_essential_Forsyth&show_result=1'>2,892</a></td><td>n/a</td><td><a href='eggs.cgi?genome=158879.1&experiment=SA_essential_Forsyth&value=essential&show_result=1'>658</a><a href='#footnotes'><sup>4</sup></a></td><td>n/a</td><td>[<a href='#ref3'>3</a>]</td></tr>
<tr><td>S. aureus N315</td><td>&nbsp;</td><td><span class='red'>*</span>SA_essential_merged_Forsyth_and_Ji</td><td colspan=9>A combined nonredundunt dataset derived from the data obtained in two similar global gene essentiality screens in S. aureus [<a href='#ref2'>2</a>, <a href='#ref3'>3</a>]</td></tr>
<tr><td>H. influenzae Rd</td><td>71421.1</td><td><span class='red'>*</span>HI_contribute_to_fitness_Akerley</td><td>random</td><td>insertion</td><td>population</td><td>Rich undefined medium BHI, 37&#176;C, aerobic growth</td><td><a href='eggs.cgi?genome=71421.1&experiment=HI_contribute_to_fitness_Akerley&show_result=1'>1,657</a></td><td><a href='eggs.cgi?genome=71421.1&experiment=HI_contribute_to_fitness_Akerley&value=nonessential&show_result=1'>602</a></td><td><a href='eggs.cgi?genome=71421.1&experiment=HI_contribute_to_fitness_Akerley&value=essential&show_result=1'>670</a></td><td>385</td><td>[<a href='#ref5'>5</a>]</td></tr>
<tr><td>S. pneumoniae R6</td><td>171101.1</td><td>SP_essential_Thanassi</td><td>targeted</td><td>insertion</td><td>clones</td><td>Rich undefined medium Todd-Hewitt, 37&#176;C, microaerobic growth in 5% CO<sub>2</sub></td><td><a href='eggs.cgi?genome=171101.1&experiment=SP_essential_Thanassi&show_result=1'>2,043</a></td><td>n/a</td><td><a href='eggs.cgi?genome=171101.1&experiment=SP_essential_Thanassi&value=essential&show_result=1'>113</a><a href='#footnotes'><sup>3</sup></a></td><td>1,696</td><td>[<a href='#ref4'>4</a>]</td></tr>
<tr><td>S. pneumoniae R6</td><td>171101.1</td><td>SP_essential_Song</td><td>targeted</td><td>deletion</td><td>clones</td><td>Rich undefined medium Todd-Hewitt, 37&#176;C, microaerobic growth in 5% CO<sub>2</sub></td><td><a href='eggs.cgi?genome=171101.1&experiment=SP_essential_Song&show_result=1'>2,043</a></td><td><a href='eggs.cgi?genome=171101.1&experiment=SP_essential_Song&value=nonessential&show_result=1'>560</a></td><td><a href='eggs.cgi?genome=171101.1&experiment=SP_essential_Song&value=essential&show_result=1'>133</a><a href='#footnotes'><sup>3</sup></a></td><td>1,350</td><td>[<a href='#ref13'>13</a>]</td></tr>
<tr><td>S. pneumoniae R6</td><td>171101.1</td><td><span class='red'>*</span>SP_essential_merged</td><td colspan=9>A combined nonredundunt dataset derived from the data obtained in two similar global gene essentiality screens in S. pneumoniae [<a href='#ref4'>4</a>, <a href='#ref13'>13</a>]</td></tr>
<tr><td>M. tuberculosis H37Rv</td><td>83332.1</td><td><span class='red'>*</span>MT_contribute_to_fitness_Rubin</td><td>random</td><td>insertion</td><td>population</td><td>Rich defined medium OADC</td><td><a href='eggs.cgi?genome=83332.1&experiment=MT_contribute_to_fitness_Rubin&show_result=1'>3,989</a></td><td><a href='eggs.cgi?genome=83332.1&experiment=MT_contribute_to_fitness_Rubin&value=nonessential&show_result=1'>2,567</a></td><td><a href='eggs.cgi?genome=83332.1&experiment=MT_contribute_to_fitness_Rubin&value=essential&show_result=1'>614</a></td><td>808</td><td>[<a href='#ref6'>6</a>]</td></tr>
<tr><td>B. subtilis 168</td><td>224308.1</td><td><span class='red'>*</span>BS_essential_Kobayashi</td><td>targeted</td><td>insertion</td><td>clones</td><td>Rich undefined medium LB, 37&#176;C, aerobic growth</td><td><a href='eggs.cgi?genome=224308.1&experiment=BS_essential_Kobayashi&show_result=1'>4,105</a></td><td><a href='eggs.cgi?genome=224308.1&experiment=BS_essential_Kobayashi&value=nonessential&show_result=1'>3,830</a><a href='#footnotes'><sup>5</sup></a></td><td><a href='eggs.cgi?genome=224308.1&experiment=BS_essential_Kobayashi&value=essential&show_result=1'>271</a><a href='#footnotes'><sup>5</sup></a></td><td>4</td><td>[<a href='#ref7'>7</a>]</td></tr>
<tr><td>E. coli K-12 MG1655</td><td>83333.1</td><td>EC_contribute_to_fitness</td><td>random</td><td>insertion</td><td>population</td><td>Rich undefined medium LB, 37&#176;C, aerobic growth</td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_contribute_to_fitness&show_result=1'>4,308</a></td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_contribute_to_fitness&value=nonessential&show_result=1'>3,126</a></td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_contribute_to_fitness&value=essential&show_result=1'>620</a></td><td>562</td><td>[<a href='#ref8'>8</a>]</td></tr>
<tr><td>E. coli K-12 MG1655</td><td>83333.1</td><td>EC_essential_Blattner</td><td>targeted</td><td>insertion</td><td>clones</td><td>Rich undefined medium LB, 37&#176;C, aerobic growth</td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_essential_Blattner&show_result=1'>4,308</a></td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_essential_Blattner&value=nonessential&show_result=1'>2,001</a></td><td>n/a</td><td>n/a</td><td>[<a href='#ref12'>12</a>]</td></tr>
<tr><td>E. coli K-12 BW25113</td><td>83333.1</td><td><span class='red'>*</span>EC_essential_Keio</td><td>targeted</td><td>deletion</td><td>clones</td><td>Rich undefined medium LB, 37&#176;C, aerobic growth</td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_essential_Keio&show_result=1'>4,390</a></td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_essential_Keio&value=nonessential&show_result=1'>3,985</a></td><td><a href='eggs.cgi?genome=83333.1&experiment=EC_essential_Keio&value=essential&show_result=1'>303</a></td><td>102</td><td>[<a href='#ref15'>15</a>]</td></tr>
<tr><td>P. aeruginosa PAO1</td><td>208964.1</td><td>PA_candidate_essential_Jacobs<a href='#footnotes'><sup>1</sup></a></td><td>random</td><td>insertion</td><td>clones</td><td>Rich undefined medium LB, room temp, aerobic growth</td><td><a href='eggs.cgi?genome=208964.1&experiment=PA_candidate_essential_Jacobs&show_result=1'>5,570</a></td><td><a href='eggs.cgi?genome=208964.1&experiment=PA_candidate_essential_Jacobs&value=nonessential&show_result=1'>4,783</a></td><td><a href='eggs.cgi?genome=208964.1&experiment=PA_candidate_essential_Jacobs&value=essential&show_result=1'>787</a></td><td>0</td><td>[<a href='#ref9'>9</a>]</td></tr>
<tr><td>P. aeruginosa PAO1</td><td>208964.1</td><td><span class='red'>*</span>PA_essential_PA14_PAO1_Liberati<a href='#footnotes'><sup>2</sup></a></a></td><td>random</td><td>insertion</td><td>clones</td><td>Rich undefined medium LB, aerobic growth</td><td><a href='eggs.cgi?genome=208964.1&experiment=PA_essential_PA14_PAO1_Liberati&show_result=1'>5,688</a></td><td><a href='eggs.cgi?genome=208964.1&experiment=PA_essential_PA14_PAO1_Liberati&value=nonessential&show_result=1'>4,469</a></td><td><a href='eggs.cgi?genome=208964.1&experiment=PA_essential_PA14_PAO1_Liberati&value=essential&show_result=1'>335</a><a href='#footnotes'><sup>2</sup></a></td><td>884</td><td>[<a href='#ref16'>16</a>]</td></tr>
<tr><td>S. typhimurium LT2</td><td>99287.1</td><td><span class='red'>*</span>ST_essential_Knuth</td><td>random</td><td>insertion</td><td>clones</td><td>Rich undefined medium LB, 30&#176;C, aerobic growth</td><td><a href='eggs.cgi?genome=99287.1&experiment=ST_essential_Knuth&show_result=1'>4,425</a></td><td>n/a</td><td><a href='eggs.cgi?genome=99287.1&experiment=ST_essential_Knuth&value=essential&show_result=1'>257</a><a href='#footnotes'><sup>3</sup></a></td><td>n/a</td><td>[<a href='#ref10'>10</a>]</td></tr>
<tr><td>H. pylori G27</td><td>85962.1</td><td><span class='red'>*</span>HP_candidate_essential_Salama<a href='#footnotes'><sup>1</sup></a></td><td>random</td><td>insertion</td><td>population</td><td>Rich undefined medium HB,  37&#176;C, microaerobic growth in 10% CO<sub>2</sub></td><td><a href='eggs.cgi?genome=85962.1&experiment=HP_candidate_essential_Salama&show_result=1'>1,576</a></td><td><a href='eggs.cgi?genome=85962.1&experiment=HP_candidate_essential_Salama&value=nonessential&show_result=1'>1,178</a></td><td><a href='eggs.cgi?genome=85962.1&experiment=HP_candidate_essential_Salama&value=essential&show_result=1'>344</a></td><td>54</td><td>[<a href='#ref11'>11</a>]</td></tr>
</table>~;
    
    $content .= "</div>";

    return $content;
}


sub get_references {
    my $content = "";

    $content .= "<hr /><div class='box'>";

    $content .= "<h4>References</h4><a href='#top'>back to top</a>
<ul><a name=ref1 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=10591650'>1. Hutchison CA, Peterson SN, Gill SR, Cline RT, White O, Fraser CM, Smith HO, Venter JC: Global transposon mutagenesis and a minimal mycoplasma genome. Science 1999, 286:2165-2169.</a></ul>
<ul><a name=ref2 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=11567142'>2. Ji YD, Zhang B, Van Horn SF, Warren P, Woodnutt G, Burnham MKR, Rosenberg M: Identification of critical staphylococcal genes using conditional phenotypes generated by antisense RNA. Science 2001, 293:2266-2269.</a></ul>
<ul><a name=ref3 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=11952893'>3. Forsyth RA, Haselbeck RJ, Ohlsen KL, Yamamoto RT, Xu H, Trawick JD, Wall D, Wang LS, Brown-Driver V, Froelich JM, et al.: A genome-wide strategy for the identification of essential genes in Staphylococcus aureus. Molecular Microbiology 2002, 43:1387-1400.</a></ul>
<ul><a name=ref4 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=12136097'>4. Thanassi JA, Hartman-Neumann SL, Dougherty TJ, Dougherty BA, J. PM: Identification of 113 conserved essential genes using a high-throughput gene disruption system in Streptococcus pneumoniae. Nucleic Acids Res. 2002, 30:3152-3162.</a></ul>
<ul><a name=ref5 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=11805338'>5. Akerley BJ, Rubin EJ, Novick VL, Amaya K, Judson N, Mekalanos JJ: A genome-scale analysis for identification of genes required for growth or survival of Haemophilus influenzae. Proc Natl Acad Sci U S A 2002, 99:966-971.</a></ul>
<ul><a name=ref6 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=12657046'>6. Sassetti CM, Boyd DH, Rubin EJ: Genes required for mycobacterial growth defined by high density mutagenesis. Mol Microbiol 2003, 48:77-84.</a></ul>
<ul><a name=ref7 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=12682299'>7. Kobayashi K, Ehrlich SD, Albertini A, Amati G, Andersen KK, Arnaud M, Asai K, Ashikaga S, Aymerich S, Bessieres P, et al.: Essential Bacillus subtilis genes. Proc Natl Acad Sci U S A 2003, 100:4678-4683.</a></ul>
<ul><a name=ref8 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=13129938'>8. Gerdes S, Scholle M, Campbell J, Balazsi G, Ravasz E, Daugherty M, Somera AL, Kyrpides N, Anderson I, Gelfand MS, et al.: Experimental determination and system-level analysis of essential genes in E. coli MG1655. J. Bacteriol. 2003, 185:5673-5684.</a></ul>
<ul><a name=ref9 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14617778'>9. Jacobs MA, Alwood A, Thaipisuttikul I, Spencer D, Haugen E, Ernst S, Will O, Kaul R, Raymond C, Levy R, et al.: Comprehensive transposon mutant library of Pseudomonas aeruginosa. Proc Natl Acad Sci U S A 2003, 100:14339-14344.</a></ul>
<ul><a name=ref10 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15009898'>10. Knuth K, Niesalla H, Hueck CJ, Fuchs TM: Large-scale identification of essential Salmonella genes by trapping lethal insertions. Mol Microbiol 2004, 51:1729-1744.</a></ul>
<ul><a name=ref11 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15547264'>11. Salama NR, Shepherd B, Falkow S: Global transposon mutagenesis and essential gene analysis of Helicobacter pylori. J Bacteriol 2004, 186:7926-7935.</a></ul>
<ul><a name=ref12 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15262929'>12. Kang Y, Durfee T, Glasner JD, Qiu Y, Frisch D, Winterberg KM, Blattner FR: Systematic mutagenesis of the Escherichia coli genome. J Bacteriol 2004, 186:4921-4930.</a></ul>
<ul><a name=ref13 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15995353'>13. Song JH, Ko KS, Lee JY, Baek JY, Oh WS, Yoon HS, Jeong JY, Chun J: Identification of essential genes in Streptococcus pneumoniae by allelic replacement mutagenesis. Mol Cells 2005, 19:365-374.</a></ul>
<ul><a name=ref14 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=16407165'>14. Glass JI, Assad-Garcia N, Alperovich N, Yooseph S, Lewis MR, Maruf M, Hutchison CA, 3rd, Smith HO, Venter JC: Essential genes of a minimal bacterium. Proc Natl Acad Sci U S A 2006, 103:425-430.</a></ul>
<ul><a name=ref15 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=16738554'>15. Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, Datsenko KA, Tomita M, Wanner BL, Mori H: Construction of Escherichia coli K-12 in-frame, single-gene knock-out mutants: the Keio collection. Mol. Systems Biol. 2006, doi:10.1038/msb4100050.</a></ul>
<ul><a name=ref16 target=_blank href='http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=16477005'>16. Liberati NT, Urbach JM, Miyata S, Lee DG, Drenkard E, Wu G, Villanueva J, Wei T, Ausubel FM: An ordered, nonredundant library of Pseudomonas aeruginosa strain PA14 transposon insertion mutants. Proc Natl Acad Sci U S A 2006.</a></ul>
";

    $content .= "</div><br /><br /><br /><br />";

    return $content;
}

MCS Webmaster
ViewVC Help
Powered by ViewVC 1.0.3