TB Genome Annotation Portal

Rv0704 (rplB)

Amino Acid Sequence

MAIRKYKPTTPGRRGASVSDFAEITRSTPEKSLVRPLHGRGGRNAHGRITTRHKGGGHKRAYRMIDFRRNDKDGVNAKVAHIEYDPNRTARIALLHYLDG
EKRYIIAPNGLSQGDVVESGANADIKPGNNLPLRNIPAGTLIHAVELRPGGGAKLARSAGSSIQLLGKEASYASLRMPSGEIRRVDVRCRATVGEVGNAE
QANINWGKAGRMRWKGKRPSVRGVVMNPVDHPHGGGEGKTSGGRHPVSPWGKPEGRTRNANKSSNKFIVRRRRTGKKHSR
(Nucleotide sequence available on KEGG)

Additional Information



ESSENTIALITY

MtbTnDB - interactive tool for exploring a database of published TnSeq datasets for Mtb

TnSeqCorr - genes with correlated TnSeq profiles across >100 conditions *new*

Classification Condition Strain Method Reference Notes
Essential Sodium Oleate H37RvMA Gumbel Subhalaxmi Nambi Probability of Essentiality: 0.999900;
17 non-insertions in a row out of 17 sites
Essential Lignoceric Acid H37RvMA Gumbel Subhalaxmi Nambi Probability of Essentiality: 1.000000;
17 non-insertions in a row out of 17 sites
Essential Phosphatidylcholine H37RvMA Gumbel Subhalaxmi Nambi Probability of Essentiality: 1.000000;
17 non-insertions in a row out of 17 sites
Essential minimal media + 0.1% glycerol H37RvMA Gumbel Griffin et al. (2011) Probability of Essentiality: 1.000000;
18 non-insertions in a row out of 18 sites
Essential minimal media + 0.01% cholesterol H37RvMA Gumbel Griffin et al. (2011) Probability of Essentiality: 1.000000;
18 non-insertions in a row out of 18 sites
Essential 7H10-glycerol H37RvMA TraSH Sassetti et al. (2003a)
Essential C57BL/6J mice (8 weeks) H37RvMA TraSH Sassetti et al. (2003b) Hybridization Ratio: 0.03
Essential 7H09/7H10 + rich media H37RvMA MotifHMM DeJesus et al. (2017) Fully saturated (14 reps).

TnSeq Data No data currently available.
  • No TnSeq data currently available for this Target.
RNASeq Data No data currently available.
  • No RNA-Seq data currently available for this Target.
Metabolomic Profiles No data currently available.
  • No Metabolomic data currently available for this Target.
Proteomic Data No data currently available.
  • No Proteomic data currently available for this Target.

Regulatory Relationships from Systems Biology
  • BioCyc

    Gene interactions based on ChIPSeq and Transcription Factor Over-Expression (TFOE) (Systems Biology)

    NOTE: Green edges represent the connected genes being classified as differentially essential as a result of the middle gene being knocked out. These interactions are inferred based on RNASeq.

    Interactions based on ChIPSeq data

    RNA processing and modification
    Energy production and conversion
    Chromatin structure and dynamics
    Amino acid transport and metabolism
    Cell cycle control, cell division, chromosome partitioning
    Carbohydrate transport and metabolism
    Nucleotide transport and metabolism
    Lipid transport and metabolism
    Coenzyme transport and metabolism
    Transcription
    Translation, ribosomal structure and biogenesis
    Cell wall/membrane/envelope biogenesis
    Replication, recombination and repair
    Posttranslational modification, protein turnover, chaperones
    Cell motility
    Secondary metabolites biosynthesis, transport and catabolism
    Inorganic ion transport and metabolism
    Function unknown
    General function prediction only
    Intracellular trafficking, secretion, and vesicular transport
    Signal transduction mechanisms
    Extracellular structures
    Defense mechanisms
    Nuclear structure
    Cytoskeleton
  • BioCyc Co-regulated genes based on gene expression profiling (Systems Biology, Inferelator Network)
  • Differentially expressed as result of RNASeq in glycerol environment (Only top 20 genes shown sorted by log fold change with p_adj 0.05).
    Conditionally essential as result of TNSeq (Only top 20 genes shown sorted by log fold change with p_adj 0.05).
  • BioCyc Transcription factor binding based on ChIP-Seq (Systems Biology)
  • Interactions based on ChIPSeq data (Minch et al. 2014)

    Interactions based on TFOE data (Rustad et al. 2014)



    TBCAP

    Tubculosis Community Annotation Project (
    Slayden et al., 2013)

    Rv0704 (rplB)

    PropertyValueCreatorEvidencePMIDComment
    InteractionPhysicalInteraction Rv0719anshula.arora1990IEPco-expression
    authors,L. Tailleux,SJ. Waddell,M. Pelizzola,A. Mortellaro,M. Withers,A. Tanne,PR. Castagnoli,B. Gicquel,NG. Stoker,PD. Butcher,M. Foti,O. Neyrolles Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages. PLoS ONE 2008
    InteractionPhysicalInteraction Rv0719anshula.arora1990IEPco-expression
    authors,I. Medow,S. Rsch-Gerdes,KH. Schrder Comparison of ribosomes and ribosomal proteins of sensitive and resistant mycobacteria. Zentralbl Bakteriol Mikrobiol Hyg A 1987
    InteractionPhysicalInteraction Rv0709ravirajsoniIEPCo-expression (Functional linkage)
    authors,R. Wang,JT. Prince,EM. Marcotte Mass spectrometry of the M. smegmatis proteome: protein expression levels correlate with function, operons, and codon bias. Genome Res. 2005
    InteractionPhysicalInteraction Rv0708ravirajsoniIEPCo-expression (Functional linkage)
    authors,R. Wang,JT. Prince,EM. Marcotte Mass spectrometry of the M. smegmatis proteome: protein expression levels correlate with function, operons, and codon bias. Genome Res. 2005
    InteractionPhysicalInteraction Rv0707ravirajsoniIEPCo-expression (Functional linkage)
    authors,R. Wang,JT. Prince,EM. Marcotte Mass spectrometry of the M. smegmatis proteome: protein expression levels correlate with function, operons, and codon bias. Genome Res. 2005
    InteractionPhysicalInteraction Rv0705ravirajsoniIEPCo-expression (Functional linkage)
    authors,R. Wang,JT. Prince,EM. Marcotte Mass spectrometry of the M. smegmatis proteome: protein expression levels correlate with function, operons, and codon bias. Genome Res. 2005
    InteractionPhysicalInteraction Rv0703ravirajsoniIEPCo-expression (Functional linkage)
    authors,R. Wang,JT. Prince,EM. Marcotte Mass spectrometry of the M. smegmatis proteome: protein expression levels correlate with function, operons, and codon bias. Genome Res. 2005
    InteractionRegulatory Rv0703ravirajsoniIPIChIP (Physical interaction)
    authors,S. Rodrigue,J. Brodeur,PE. Jacques,AL. Gervais,R. Brzezinski,L. Gaudreau Identification of mycobacterial sigma factor binding sites by chromatin immunoprecipitation assays. J. Bacteriol. 2007
    InteractionRegulatedBy Rv0348yamir.morenoIEPMicroarrays. mRNA levels of regulated element measured and compared between wild-type and trans-element mutation (knockout, over expression etc.) performed by using microarray (or macroarray) experiments..
    B. Abomoelak, EA. Hoye et al. mosR, a novel transcriptional regulator of hypoxia and virulence in Mycobacterium tuberculosis. J. Bacteriol. 2009

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