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pmid:34484169

The Role of graRS in Regulating Virulence and Antimicrobial Resistance in Methicillin-Resistant Staphylococcus aureus.

Le Chen · Zihui Wang · Tao Xu · Hongfei Ge · Fangyue Zhou · Xiaoyi Zhu · Xianhui Li · Di Qu · Chunquan Zheng · Yang Wu · Keqing Zhao

Frontiers in microbiology · 2021 doi:10.3389/fmicb.2021.727104

Paper

complete

Experiment

partial

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:34484169
kind
science-record
content_hash
sha256:0ae0abf240f9072c14fc253d357967d6bede8f7eb6a6a99d6921481383a33b1f
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:41:50Z
updated_at
2026-11-01T21:26:09Z
generator object · 2 fields
name
corpus-assay-engine
run_id
reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
The Role of graRS in Regulating Virulence and Antimicrobial Resistance in Methicillin-Resistant Staphylococcus aureus.
doi
10.3389/fmicb.2021.727104
pmid
34484169
authors array · 11 items
[0]
Le Chen
[1]
Zihui Wang
[2]
Tao Xu
[3]
Hongfei Ge
[4]
Fangyue Zhou
[5]
Xiaoyi Zhu
[6]
Xianhui Li
[7]
Di Qu
[8]
Chunquan Zheng
[9]
Yang Wu
[10]
Keqing Zhao
journal
Frontiers in microbiology
year
2021
abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is a common cause of both community- and hospital-associated infections. The antibiotic resistance and virulence characteristics of MRSA are largely regulated by two-component signal transduction systems (TCS) including the graRS TCS. To make a relatively comprehensive insight into graRS TCS in MRSA, the bioinformatics analysis of dataset GSE26016 (a S. aureus HG001 WT strain vs. the ΔgraRS mutant) from Gene Expression Omnibus (GEO) database was performed, and a total of 563 differentially expressed genes (DEGs) were identified. GO analysis revealed that the DEGs were mainly enriched in the "de novo" IMP biosynthetic process, lysine biosynthetic process via diaminopimelate, and pathogenesis; and they were mainly enriched in purine metabolism, lysine biosynthesis, and monobactam biosynthesis in KEGG analysis. WGCNA suggested that the turquoise module was related to the blue module, and the genes in these two modules were associated with S. aureus virulence and infection. To investigate the role of graRS in bacterial virulence, a graRS knockout mutant (ΔgraRS) was constructed using MRSA USA500 2,395 strain as a parent strain. Compared to the wild-type strain, the USA500ΔgraRS showed reduced staphyloxanthin production, retarded coagulation, weaker hemolysis on blood agar plates, and a decreased biofilm formation. These altered phenotypes were restored by the complementation of a plasmid-expressed graRS. Meanwhile, an expression of the virulence-associated genes (coa, hla, hlb, agrA, and mgrA) was downregulated in the ΔgraRS mutant. Consistently, the A549 epithelial cells invasion of the ΔgraRS mutant was 4-fold lower than that of the USA500 wild-type strain. Moreover, on the Galleria mellonella infection model, the survival rate at day 5 post infection in the USA500ΔgraRS group (55%) was obviously higher than that in the USA500 group (20%), indicating graRS knockout leads to a decreased virulence in vivo. In addition, the deletion of the graRS in the MRSA USA500 strain resulted in its increased susceptibilities to ampicillin, oxacillin, vancomycin, and gentamicin. Our work suggests that the graRS TCS plays an important role in regulating S. aureus virulence in vitro and in vivo and modulate bacterial resistance to various antibiotics.
claims array · 2 items
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Kaplan–Meier analysis was performed for the survival plots of in vivo infection. A log-rank test was carried out for comparison of survival curves.
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methodological
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null
evidence array · 1 item
[0] object · 3 fields
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locator
sections[19] "Statistical Analysis" paragraph 2
quote
Kaplan–Meier analysis was performed for the survival plots of in vivo infection. A log-rank test was carried out for comparison of survival curves.
state
complete
[1] object · 6 fields
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claim-data-access
statement
The original contributions presented in the study are included in the article/Supplementary Material, and further inquiries can be directed to the corresponding author/s.
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methodological
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null
evidence array · 1 item
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source:pmid:34484169
locator
sections[31] "Data Availability Statement" paragraph 2
quote
The original contributions presented in the study are included in the article/Supplementary Material, and further inquiries can be directed to the corresponding author/s.
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complete
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null
steps array · 3 items
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Read the published estimate from the source
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other
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The claim, method and evidence span published with the source article.
parameters object · 0 fields
inputs array · 1 item
[0]
source:pmid:34484169
outputs array · 1 item
[0]
the published estimate and its evidence
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reagents array · 0 items
[1] object · 13 fields
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obtain_source_data
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Obtain the source data from the named repository
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The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.
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inputs array · 0 items
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[0]
the source data with its repository provenance
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Run the published analysis
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Apply the paper's statistical method to the resolved series and compare the result with the published target.
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the replicated result and its comparison
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application/xml
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https://doi.org/10.3389/fmicb.2021.727104
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10.3389/fmicb.2021.727104
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Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.
structure object · 4 fields
pmcid
PMC8415711
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europe_pmc_fulltext
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whole_body
text_hash_scope
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[1] object · 16 fields
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asset:table:pmid:34484169:1
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Primers used in this study.
structure object · 5 fields
pmcid
PMC8415711
section_index
10
section_title
RNA Extraction and Quantitative Real-Time-PCR
row_count
63
column_count
2
table object · 8 fields
label
Table 1
caption
Primers used in this study.
rows array · 63 items
[0] array · 2 items
[0]
Primers
[1]
Sequence (5' → 3')
[1] array · 2 items
[0]
gyrB(F)
[1]
ACATTACAGCAGCGTATTAG
[2] array · 2 items
[0]
gyrB(R)
[1]
CTCATAGTGATAGGAGTCTTCT
[3] array · 2 items
[0]
graR(F)
[1]
GTTGCTGGTATTGAAGATT
[4] array · 2 items
[0]
graR(R)
[1]
GTTCCATACTCATCACTTG
[5] array · 2 items
[0]
graS(F)
[1]
TTACTATATGAATGGTCTCGTAT
[6] array · 2 items
[0]
graS(R)
[1]
ACCTGACTAATATGTCTTGTT
[7] array · 2 items
[0]
vraF(F)
[1]
AAGAAGTGTTGCGAGATA
[8] array · 2 items
[0]
vraF(R)
[1]
ATGCTTGCGTATATCAGA
[9] array · 2 items
[0]
vraG(F)
[1]
GTTAATCGGTGTCGCTTAT
[10] array · 2 items
[0]
vraG(R)
[1]
ATCCTGTGGTAATCAATACTATAC
[11] array · 2 items
[0]
dltX(F)
[1]
GCCACCTAATAAATATGTTGAAGC
[12] array · 2 items
[0]
dltX(R)
[1]
GTGTCGCCACTGCCATAA
[13] array · 2 items
[0]
dltA(F)
[1]
GAAGGTGAACTTGTTATCG
[14] array · 2 items
[0]
dltA(R)
[1]
TTCCATTCTGTAGCCATT
[15] array · 2 items
[0]
mprF(F)
[1]
CGCTATTACTTCTGGCTTACG
[16] array · 2 items
[0]
mprF(R)
[1]
AATAATCTCCTCGCAATCTTCAAT
[17] array · 2 items
[0]
mecA(F)
[1]
TTAATAAGTGAGGTGCGTTA
[18] array · 2 items
[0]
mecA(R)
[1]
TAGGTGTTGGTGAAGATATAC
[19] array · 2 items
[0]
mecR1(F)
[1]
GATTAAGGCATTCCGACAA
[20] array · 2 items
[0]
mecR1(R)
[1]
CGACTACGACAGTTGGTA
[21] array · 2 items
[0]
femA(F)
[1]
GCTGAAGATGCTGGTGTAGTT
[22] array · 2 items
[0]
femA(R)
[1]
GTGCGGTATATGCTGCGTAA
[23] array · 2 items
[0]
femB(F)
[1]
TTCTCTGGTGGTTCATCA
[24] array · 2 items
[0]
femB(R)
[1]
CGCCATAATCTTCACTGTT
[25] array · 2 items
[0]
pbp1(F)
[1]
AAGTGCCAGATGTTGAAGG
[26] array · 2 items
[0]
pbp 1(R)
[1]
GTGTGCCAGAACCAATAGTAA
[27] array · 2 items
[0]
pbp 2(F)
[1]
ACACCTCAATACACTATG
[28] array · 2 items
[0]
pbp 2(R)
[1]
GGATACTACCACTTACTG
[29] array · 2 items
[0]
pbp 3(F)
[1]
TTCAGCCGTATCCAACATT
[30] array · 2 items
[0]
pbp 3(R)
[1]
GTGCCAAGAGGTCGTATT
[31] array · 2 items
[0]
pbp 4(F)
[1]
TATGAACAATAAGTGCTAATCC
[32] array · 2 items
[0]
pbp 4(R)
[1]
GACCTCCAACTGTAGAAG
[33] array · 2 items
[0]
fmtA(F)
[1]
TAACCAATCCATTATTACAT
[34] array · 2 items
[0]
fmtA(R)
[1]
ACAACTACATACTTATCATTA
[35] array · 2 items
[0]
fmtB(F)
[1]
ATTGCTAATGCTTCAGTT
[36] array · 2 items
[0]
fmtB(R)
[1]
ATAATGGTGTGGATAATGG
[37] array · 2 items
[0]
glmM(F)
[1]
TGGATTATGAGAGGCTGAA
[38] array · 2 items
[0]
glmM(R)
[1]
GAAGTGATGCGATTAGGTATT
[39] array · 2 items
[0]
fmtC(F)
[1]
CGCTATTACTTCTGGCTTACG
[40] array · 2 items
[0]
fmtC(R)
[1]
AATAATCTCCTCGCAATCTTCAAT
[41] array · 2 items
[0]
abcA(F)
[1]
GAACCTATTGAACCGACAGAA
[42] array · 2 items
[0]
abcA(R)
[1]
TTGGAACGACACATCATCTAAT
[43] array · 2 items
[0]
trfA(F)
[1]
GCATATCATAGCAATCCAAT
[44] array · 2 items
[0]
trfA(R)
[1]
ACTTCTGTTCTGTCTGTT
[45] array · 2 items
[0]
llm(F)
[1]
CTGCCTTAGTAGTTGCTT
[46] array · 2 items
[0]
llm(R)
[1]
CTATTGTAATGAGTCCGATTG
[47] array · 2 items
[0]
flp(F)
[1]
CCAATGATTCGCAACAACA
[48] array · 2 items
[0]
flp(R)
[1]
CAACATCTTGATAACCATAACCTT
[49] array · 2 items
[0]
prfp(F)
[1]
AACGCTTGTTGTAAGATT
[50] array · 2 items
[0]
prfp(R)
[1]
TGTTGTAAGTCAATTAGAGG
[51] array · 2 items
[0]
mdh(F)
[1]
GCACTTCCAATTACTGTT
[52] array · 2 items
[0]
mdh(R)
[1]
GCAGGTAGACTATATCGT
[53] array · 2 items
[0]
spx(F)
[1]
GTTGATATTGATTCACTACCA
[54] array · 2 items
[0]
spx(R)
[1]
CGTTGTGCTTCTTGTAAT
[55] array · 2 items
[0]
mgrA(F)
[1]
TACCTAATAAGCGATTAAGTT
[56] array · 2 items
[0]
mgrA(R)
[1]
AACGAATGGAACAAGTAG
[57] array · 2 items
[0]
norG(F)
[1]
GCACCAGCAATAAGAATAGG
[58] array · 2 items
[0]
norG(R)
[1]
TTCAACATCTCATATACAACCATT
[59] array · 2 items
[0]
sigB(F)
[1]
TTCCATTGCTTCTAACACTT
[60] array · 2 items
[0]
sigB(R)
[1]
GATGAACTAACCGCTGAAT
[61] array · 2 items
[0]
agrA(F)
[1]
GCAGTAATTCAGTGTATGTTCA
[62] array · 2 items
[0]
agrA(R)
[1]
TATGGCGATTGACGACAA
locator
section[10]/table-wrap[1]#tab1
[2] object · 16 fields
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asset:table:pmid:34484169:2
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jats-table
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read_table
reader_status
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section[24]/table-wrap[1]#tab2
version
null
note
The number of mRNAs contained in different modules (top six modules).
structure object · 5 fields
pmcid
PMC8415711
section_index
24
section_title
Co-expression Network Analysis of GSE26016
row_count
4
column_count
4
table object · 8 fields
label
Table 2
caption
The number of mRNAs contained in different modules (top six modules).
rows array · 4 items
[0] array · 4 items
[0]
Modules*
[1]
Freq*
[2]
Modules
[3]
Freq
[1] array · 4 items
[0]
Turquoise
[1]
964
[2]
Blue
[3]
497
[2] array · 4 items
[0]
Grey
[1]
407
[2]
Brown
[3]
332
[3] array · 4 items
[0]
Yellow
[1]
134
[2]
Green
[3]
52
locator
section[24]/table-wrap[1]#tab2
[3] object · 16 fields
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asset:table:pmid:34484169:3
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table
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jats-table
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application/vnd.jats.table+json
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null
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read_table
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section[24]/table-wrap[2]#tab3
version
null
note
GO and KEGG enrichment analyses of module blue and turquoise constructed by WGCNA (p < 0.05, count ≥ 10).
structure object · 5 fields
pmcid
PMC8415711
section_index
24
section_title
Co-expression Network Analysis of GSE26016
row_count
25
column_count
4
table object · 8 fields
label
Table 3
caption
GO and KEGG enrichment analyses of module blue and turquoise constructed by WGCNA (p < 0.05, count ≥ 10).
rows array · 25 items
[0] array · 4 items
[0]
Module
[1]
Term
[2]
Count
[3]
p
[1] array · 4 items
[0]
Turquoise_GO
[1]
GO:0006189~“de novo” IMP biosynthetic process
[2]
11
[3]
0.002
[2] array · 3 items
[0]
GO:0019843~rRNA binding
[1]
22
[2]
0.004
[3] array · 3 items
[0]
GO:0022625~cytosolic large ribosomal subunit
[1]
16
[2]
0.005
[4] array · 3 items
[0]
GO:0000287~magnesium ion binding
[1]
36
[2]
0.007
[5] array · 3 items
[0]
GO:0003735~structural constituent of ribosome
[1]
29
[2]
0.012
[6] array · 3 items
[0]
GO:0005737~cytoplasm
[1]
145
[2]
0.016
[7] array · 3 items
[0]
GO:0051287~NAD binding
[1]
13
[2]
0.047
[8] array · 4 items
[0]
Turquoise_KEGG
[1]
sao01110: Biosynthesis of secondary metabolites
[2]
108
[3]
0.000
[9] array · 3 items
[0]
sao00230: Purine metabolism
[1]
34
[2]
0.001
[10] array · 3 items
[0]
sao01130: Biosynthesis of antibiotics
[1]
76
[2]
0.002
[11] array · 3 items
[0]
sao00300: Lysine biosynthesis
[1]
11
[2]
0.004
[12] array · 3 items
[0]
sao01100: Metabolic pathways
[1]
183
[2]
0.007
[13] array · 3 items
[0]
sao01210:2-Oxocarboxylic acid metabolism
[1]
14
[2]
0.009
[14] array · 3 items
[0]
sao01230: Biosynthesis of amino acids
[1]
51
[2]
0.010
[15] array · 3 items
[0]
sao00290: Valine, leucine, and isoleucine biosynthesis
[1]
10
[2]
0.017
[16] array · 3 items
[0]
sao00770: Pantothenate and CoA biosynthesis
[1]
11
[2]
0.031
[17] array · 3 items
[0]
sao03018: RNA degradation
[1]
10
[2]
0.033
[18] array · 4 items
[0]
Blue_GO
[1]
GO:0005576~extracellular region
[2]
35
[3]
0.000
[19] array · 3 items
[0]
GO:0009405~pathogenesis
[1]
28
[2]
0.000
[20] array · 3 items
[0]
GO:0003735~structural constituent of ribosome
[1]
15
[2]
0.010
[21] array · 3 items
[0]
GO:0009401~phosphoenolpyruvate-dependent sugar phosphotransferase system
[1]
11
[2]
0.010
[22] array · 3 items
[0]
GO:0016020~membrane
[1]
11
[2]
0.034
[23] array · 4 items
[0]
Blue_KEGG
[1]
sao00052: Galactose metabolism
[2]
13
[3]
0.000
[24] array · 3 items
[0]
sao05150: Staphylococcus aureus infection
[1]
11
[2]
0.010
locator
section[24]/table-wrap[2]#tab3
[4] object · 16 fields
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asset:table:pmid:34484169:4
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table
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jats-table
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application/vnd.jats.table+json
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null
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512
access
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verified
reader
read_table
reader_status
available
identifier
section[29]/table-wrap[1]#tab4
version
null
note
The MIC of ampicillin, gentamicin, oxacillin, and vancomycin for different Staphylococcus aureus strains (the broth microdilution method).
structure object · 5 fields
pmcid
PMC8415711
section_index
29
section_title
Effect of graRS Mutation in USA500 on the Antimicrobial Susceptibilities
row_count
6
column_count
5
table object · 8 fields
label
Table 4
caption
The MIC of ampicillin, gentamicin, oxacillin, and vancomycin for different Staphylococcus aureus strains (the broth microdilution method).
rows array · 6 items
[0] array · 2 items
[0]
[1]
MIC*
[1] array · 5 items
[0]
[1]
Ampicillin
[2]
Oxacillin
[3]
Vancomycin
[4]
Gentamicin
[2] array · 5 items
[0]
USA500WT
[1]
>8
[2]
>8
[3]
1
[4]
4
[3] array · 5 items
[0]
USA500ΔgraRS
[1]
2
[2]
2
[3]
0.25
[4]
0.5
[4] array · 5 items
[0]
USA500ΔgraRS:: pRB475-graRS
[1]
8
[2]
>8
[3]
1
[4]
4
[5] array · 5 items
[0]
ATCC29213
[1]
2
[2]
0.125
[3]
0.5
[4]
1
locator
section[29]/table-wrap[1]#tab4
gaps array · 0 items
analysis object · 4 fields
state
complete
methods array · 2 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
band
verbatim
quote
Kaplan–Meier analysis was performed for the survival plots of in vivo infection. A log-rank test was carried out for comparison of survival curves.
[1] object · 10 fields
id
method-2
family
clustering
specific
hierarchical
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Clustering
dsl_operations array · 1 item
[0]
hierarchical_cluster
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
feature_matrix
evidence object · 3 fields
score
0.8
band
high
quote
hierarchical clustering
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
blocked
tier
R4
blocked_on
data:accession_absent
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
[0]
logrank_test
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: log_rank_test.
capability object · 4 fields
tier
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data object · 6 fields
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The original contributions presented in the study are included in the article/Supplementary Material, and further inquiries can be directed to the corresponding author/s.
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ated in the ΔgraRS mutant. Consistently, the A549 epithelial cells invasion of the ΔgraRS muta
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s. The mRNA of the USA500WT and USA500ΔgraRS cultured in TSB at 4 h was extracted, then qRT-PCR was p
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raRS knockout leads to a decreased virulence in vivo. In addition, the deletion of the graRS in t
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regulating S. aureus virulence in vitro and in vivo and modulate bacterial resistance to various
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Kaplan–Meier analysis was performed for the survival plots of in vivo infection. A log-rank test was carried out for comparison of survival curves.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34484169", "kind": "science-record", "revision": 6, "content_hash": "sha256:0ae0abf240f9072c14fc253d357967d6bede8f7eb6a6a99d6921481383a33b1f", "created_at": "2026-11-01T15:41:50Z", "updated_at": "2026-11-01T21:26:09Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The Role of graRS in Regulating Virulence and Antimicrobial Resistance in Methicillin-Resistant Staphylococcus aureus.", "doi": "10.3389/fmicb.2021.727104", "pmid": "34484169", "authors": ["Le Chen", "Zihui Wang", "Tao Xu", "Hongfei Ge", "Fangyue Zhou", "Xiaoyi Zhu", "Xianhui Li", "Di Qu", "Chunquan Zheng", "Yang Wu", "Keqing Zhao"], "journal": "Frontiers in microbiology", "year": 2021, "abstract": "Methicillin-resistant Staphylococcus aureus (MRSA) is a common cause of both community- and hospital-associated infections. The antibiotic resistance and virulence characteristics of MRSA are largely regulated by two-component signal transduction systems (TCS) including the graRS TCS. To make a relatively comprehensive insight into graRS TCS in MRSA, the bioinformatics analysis of dataset GSE26016 (a S. aureus HG001 WT strain vs. the ΔgraRS mutant) from Gene Expression Omnibus (GEO) database was performed, and a total of 563 differentially expressed genes (DEGs) were identified. GO analysis revealed that the DEGs were mainly enriched in the \"de novo\" IMP biosynthetic process, lysine biosynthetic process via diaminopimelate, and pathogenesis; and they were mainly enriched in purine metabolism, lysine biosynthesis, and monobactam biosynthesis in KEGG analysis. WGCNA suggested that the turquoise module was related to the blue module, and the genes in these two modules were associated with S. aureus virulence and infection. To investigate the role of graRS in bacterial virulence, a graRS knockout mutant (ΔgraRS) was constructed using MRSA USA500 2,395 strain as a parent strain. Compared to the wild-type strain, the USA500ΔgraRS showed reduced staphyloxanthin production, retarded coagulation, weaker hemolysis on blood agar plates, and a decreased biofilm formation. These altered phenotypes were restored by the complementation of a plasmid-expressed graRS. Meanwhile, an expression of the virulence-associated genes (coa, hla, hlb, agrA, and mgrA) was downregulated in the ΔgraRS mutant. Consistently, the A549 epithelial cells invasion of the ΔgraRS mutant was 4-fold lower than that of the USA500 wild-type strain. Moreover, on the Galleria mellonella infection model, the survival rate at day 5 post infection in the USA500ΔgraRS group (55%) was obviously higher than that in the USA500 group (20%), indicating graRS knockout leads to a decreased virulence in vivo. In addition, the deletion of the graRS in the MRSA USA500 strain resulted in its increased susceptibilities to ampicillin, oxacillin, vancomycin, and gentamicin. Our work suggests that the graRS TCS plays an important role in regulating S. aureus virulence in vitro and in vivo and modulate bacterial resistance to various antibiotics.", "claims": [{"id": "claim-method", "statement": "Kaplan–Meier analysis was performed for the survival plots of in vivo infection. A log-rank test was carried out for comparison of survival curves.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34484169", "locator": "sections[19] \"Statistical Analysis\" paragraph 2", "quote": "Kaplan–Meier analysis was performed for the survival plots of in vivo infection. 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