Abstract

   Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause
   of life-threatening endovascular infections. Endothelial cell (EC)
   damage is a key factor in the pathogenesis of these syndromes. However,
   genetic factors related to the EC damage have not been well studied.
   This study aims to identify genetic determinants that impact human EC
   damage by screening the genome-wide Nebraska Transposon Mutant Library
   (NTML). A well-established MTT assay was used to test the in vitro
   damage of human EC cell line (HMEC-1) caused by each mutant strain in
   the NTML. We first confirmed some global regulators and genes
   positively impact the EC damage, which is consistent with published
   results. These data support the utility of the high-throughput
   approach. Importantly, we demonstrated 317 mutants significantly
   decreased the EC damage, while only 6 mutants enhanced the EC damage
   vs. parental JE2 strain. The majority of these genes have not been
   previously defined to affect human EC damage. Interestingly, many of
   these newly identified genes are involved in metabolism, genetic and
   environmental information processing, and cellular processes. These
   results advance our knowledge of staphylococcal genetic factors related
   to human EC damage which may provide novel targets for the development
   of effective agents against MRSA endovascular infection.

   Keywords: MRSA, human endothelial cell damage, virulence factors

1. Introduction

   Staphylococcus aureus is the most common cause of endovascular
   infection, including infective endocarditis (IE). Despite the use of
   gold-standard antibiotics, morbidity and mortality associated with
   these syndromes remain unacceptably high [[30]1]. In addition, the
   emergence of methicillin-resistant S. aureus (MRSA) further complicates
   the management of patients with these infections and emphasizes this
   public health threat [[31]1]. Therefore, there is an urgent need to
   understand specific genetic factors involved in the pathogenesis and
   antibiotic treatment outcome of MRSA endovascular infection.

   It is generally recognized that the pathogenesis of S. aureus is
   complex and probably involves the coordinate expression of multiple
   gene products, including a variety of surface adhesive proteins and
   exoproteins [[32]2]. Once S. aureus enters into the bloodstream, it
   must avoid host innate defense killing to survive. When the organism
   has persisted in the bloodstream, it must then colonize and invade the
   endothelial cells (ECs) lining of the blood vessels, and, subsequently,
   damage the ECs to infect deeper tissues to cause organ dissemination
   [[33]3]. It has been well demonstrated that EC damage plays a crucial
   role in the pathogenesis of many human diseases, including endovascular
   infections [[34]4]. In addition, we have recently demonstrated a
   positive correlation between in vitro human EC damage and virulence, as
   well as vancomycin treatment persistent outcome in an experimental
   endocarditis model caused by clinical MRSA isolates [[35]5]. However,
   little is known about the genetic factors involved in the EC damage in
   S. aureus.

   The Nebraska Transposon Mutant Library (NTML) consists of 1920
   sequence-defined transposon insertion mutants of non-essential genes in
   a community-associated (CA) MRSA USA300 strain, JE2 [[36]6]. This
   library has been used for screening several biological phenotypes,
   including hemolysis, proteolysis, carotenoid pigment formation,
   antibiotic susceptibility, and biofilm formation [[37]6,[38]7,[39]8].
   These investigations demonstrate that the NTML may serve as a valuable
   genetic tool to study host-pathogen interaction.

   Numerous investigations have used human umbilical vein EC (HUVECs) to
   study microbial–EC interactions. However, the use of HUVECs requires a
   constant supply of umbilical cords, and there are significant
   donor-to-donor variations in these ECs. To overcome these difficulties,
   immortalized ECs, including human microvascular EC (HMEC-1), have been
   developed. These cell lines have better availability and less
   variability [[40]9]. In addition, we previously compared S. aureus EC
   damage with HMEC-1 cell line and HUVECs, and found HMEC-1 cells were
   more susceptible to damage caused by S. aureus vs. HUVECs [[41]10]. In
   addition, the HMEC-1 cell line has been used to study the EC
   interactions with multiple microorganisms, including S. aureus
   [[42]10,[43]11,[44]12]. Thus, in the current investigation, the HMEC-1
   cell line was employed to test the impact of all the mutant strains in
   the NTML on its damage.

   In the current study, we aimed to identify staphylococcal genes
   associated with the EC damage by performing an unbiased genome-wide
   screening of all mutations in the NTML. This study will remarkably
   advance our understanding of staphylococcal genetic factors related to
   human EC damage which may provide novel targets for the development of
   effective compounds against MRSA endovascular infections.

2. Results

2.1. The MTT Assay Is Applicable to the High Throughput Screening of Genes
Involved in HMEC-1 Damage

   We confirmed some S. aureus genetic factors which have previously been
   reported to affect EC damage. For instance, global regulator (e.g.,
   agr, saeSR, and arlSR) and structural genes related to gamma-hemolysin
   (e.g., hlg) and serine-like protease (e.g., spl) positively impact EC
   damage. In addition, the control arlR mutant strain caused
   significantly less EC damage (<30%) vs. JE2 parental strain, which is
   in accordance with the previously reported results. These results
   proved the feasibility and reliability of this high throughput
   screening assay.

2.2. Identified Staphylococcal Genes Impacting HMEC-1 Damages

   The mean HMEC-1 damage rate caused by the JE2 parental strain is 46.19
   ± 2.97%. To focus on the genes which highly affect the EC damage, we
   set up the EC damage rates of ≤30% or ≥60% with p values less than 0.05
   as cutoffs for data analysis. Screening of the whole NTML displayed
   that 317 individual gene mutations led to significantly decreased
   HMEC-1 damage rates (≤30%; p <0.05; [45]Figure 1, [46]Table 1),
   suggesting these genes positively impact the EC damage. Only six mutant
   strains demonstrated significantly increased HMEC-1 damage (≥60%, p <
   0.05; [47]Figure 1, [48]Table 2), including four genes with known
   functions (e.g., mepA, azoR, and moaD, and SAUSA300_1197) and two
   hypothetical genes with unknown function. EC damage rates of the rest
   mutants from the NTML were presented in [49]Supplementary Table S1. JE2
   parental strain and randomly selected mutants showed similar EC damage
   rates between 24-well and 384-well plates assay ([50]Table 3). Some of
   the mutants that caused significant changes to EC damage were
   successfully classified into KEGG categories, including metabolism,
   genetic information processing, environmental information processing,
   and cellular processes ([51]Table 4). For the KEGG categories, ~65% of
   genes functioned in metabolism pathways, ~24% involved in environmental
   information processing, ~11% acted in genetic information processes,
   and ~9% associated with cellular processes ([52]Figure 2). In addition,
   some of these genes had multiple functions in the different KEGG
   pathways.

Figure 1.

   [53]Figure 1
   [54]Open in a new tab

   The global map of in vitro HMEC-1 damage rate caused by the mutant
   strains in the NTML. The vertical dashed line represents the mean of
   HMEC-1 damage rate of parental strain USA300 JE2 (46.19%); and the
   horizontal dashed line represents the p value of 0.05. The bright red
   dots represent ≤30% EC damage caused, while the bright blue dots
   represent ≥60% EC damage due to the study mutant strains in the NTML
   and p < 0.05 vs. JE2 WT strain. Damage rate below zero means the
   A[560nm] of the test well is higher than the A[560nm] of the negative
   damage control, which indicates that the mutant causes no damage to the
   EC.

Table 1.

   Mutants significantly decrease HMEC-1 damage vs. JE2 WT strain (EC
   damage rate ≤ 30%).
   Locus Gene Name Description % EC Damage
   (Mean ± SD)
   SAUSA300_0261 hypothetical conserved hypothetical protein 29.83 ± 8.34
   SAUSA300_1172 hypothetical M16 family peptidase 29.74 ± 4.80
   SAUSA300_0083 hypothetical hypothetical protein 29.70 ± 10.14
   SAUSA300_1386 hypothetical phiETA ORF59-like protein 29.57 ± 1.07
   SAUSA300_0076 hypothetical ABC transporter ATP-binding protein 29.57 ±
   4.10
   SAUSA300_1712 ribH 6,7-dimethyl-8-ribityllumazine synthase 29.49 ± 9.83
   SAUSA300_1457 malR maltose operon transcriptional repressor 29.46 ±
   2.79
   SAUSA300_1309 hypothetical IS200 family transposase 29.41 ± 8.13
   SAUSA300_1253 glcT transcription antiterminator 29.37 ± 4.04
   SAUSA300_1797 hypothetical conserved hypothetical protein 29.37 ± 4.79
   SAUSA300_1759 hypothetical hypothetical protein 29.25 ± 2.85
   SAUSA300_2386 hypothetical beta-lactamase 29.13 ± 1.62
   SAUSA300_2434 hypothetical transporter protein 29.13 ± 5.28
   SAUSA300_2037 hypothetical ATP-dependent RNA helicase 28.67 ± 8.90
   SAUSA300_1654 hypothetical proline dipeptidase 28.46 ± 4.20
   SAUSA300_0615 hypothetical putative monovalent cation/H+ antiporter
   subunit F 28.45 ± 4.24
   SAUSA300_1659 tpx thiol peroxidase 28.41 ± 7.42
   SAUSA300_1478 hypothetical putative lipoprotein 28.28 ± 4.37
   SAUSA300_2455 hypothetical putative fructose-1,6-bisphosphatase 28.27 ±
   5.83
   SAUSA300_1297 acyP acylphosphatase 28.23 ± 4.50
   SAUSA300_2606 hisF imidazole glycerol phosphate synthase subunit HisF
   27.62 ± 4.01
   SAUSA300_0795 hypothetical hypothetical protein 27.38 ± 6.00
   SAUSA300_1683 hypothetical bifunctional 3-deoxy-7-phosphoheptulonate
   synthase/chorismate mutase 27.26 ± 6.86
   SAUSA300_2618 hypothetical hypothetical protein 27.23 ± 7.65
   SAUSA300_1398 hypothetical phiSLT ORF123-like protein 27.16 ± 11.43
   SAUSA300_0059 hypothetical conserved hypothetical protein 27.07 ± 7.67
   SAUSA300_1764 epiD lantibiotic epidermin biosynthesis protein EpiD
   26.84 ± 3.46
   SAUSA300_2332 hypothetical heat shock protein 26.78 ± 8.46
   SAUSA300_1040 hypothetical hypothetical protein 26.74 ± 8.21
   SAUSA300_2280 fosB fosfomycin resistance protein FosB 26.67 ± 8.68
   SAUSA300_1750 hypothetical conserved hypothetical protein 26.62 ± 9.44
   SAUSA300_0883 hypothetical putative surface protein 26.40 ± 12.90
   SAUSA300_1964 hypothetical hypothetical protein 26.38 ± 7.19
   SAUSA300_0290 hypothetical putative lipoprotein 26.29 ± 8.56
   SAUSA300_1672 nagE phosphotransferase system,
   N-acetylglucosamine-specific IIBC component 26.21 ± 5.46
   SAUSA300_2023 rsbW anti-sigma-B factor, serine-protein kinase 26.01 ±
   0.14
   SAUSA300_0190 ipdC indole-3-pyruvate decarboxylase 25.81 ± 7.93
   SAUSA300_2413 hypothetical hypothetical protein 25.79 ± 4.70
   SAUSA300_0798 hypothetical ABC transporter substrate-binding protein
   25.59 ± 3.93
   SAUSA300_0489 ftsH putative cell division protein FtsH 25.55 ± 5.76
   SAUSA300_1093 pyrB aspartate carbamoyltransferase catalytic subunit
   25.49 ± 1.23
   SAUSA300_0517 hypothetical RNA methyltransferase 25.39 ± 8.18
   SAUSA300_1740 hypothetical hypothetical protein 25.37 ± 9.05
   SAUSA300_0540 hypothetical HAD family hydrolase 25.26 ± 9.24
   SAUSA300_2272 hypothetical hypothetical protein 25.25 ± 4.80
   SAUSA300_1968 hypothetical putative phage transcriptional regulator
   25.23 ± 9.97
   SAUSA300_0642 hypothetical hypothetical protein 25.21 ± 4.58
   SAUSA300_2358 hypothetical ABC transporter permease 25.11 ± 6.08
   SAUSA300_1984 mroQ hypothetical protein 25.07 ± 9.15
   SAUSA300_1266 trpF N-(5′-phosphoribosyl)anthranilate isomerase 25.05 ±
   7.12
   SAUSA300_2251 hypothetical dehydrogenase family protein 25.00 ± 3.65
   SAUSA300_0706 hypothetical putative osmoprotectant ABC transporter
   ATP-binding protein 24.95 ± 11.00
   SAUSA300_0941 hypothetical putative ferrichrome ABC transporter 24.69 ±
   6.43
   SAUSA300_0951 sspA V8 protease 24.55 ± 8.41
   SAUSA300_1875 hypothetical exonuclease 24.52 ± 10.68
   SAUSA300_0566 hypothetical amino acid permease 24.49 ± 5.06
   SAUSA300_0871 hypothetical hypothetical protein 24.49 ± 12.19
   SAUSA300_0565 hypothetical conserved hypothetical protein 24.43 ± 5.34
   SAUSA300_0391 hypothetical hypothetical protein 24.38 ± 0.45
   SAUSA300_1328 hypothetical putative drug transporter 24.10 ± 7.38
   SAUSA300_2279 hypothetical LysR family regulatory protein 23.92 ± 10.37
   SAUSA300_0505 hypothetical glutamine amidotransferase subunit PdxT
   23.61 ± 3.46
   SAUSA300_0470 ksgA dimethyladenosine transferase 23.56 ± 7.13
   SAUSA300_1106 hypothetical putative lipoprotein 23.45 ± 8.92
   SAUSA300_1991 agrC accessory gene regulator protein C 23.44 ± 9.71
   SAUSA300_0108 hypothetical antigen, 67 kDa 23.33 ± 6.80
   SAUSA300_2326 araC transcription regulatory protein 23.30 ± 5.35
   SAUSA300_1399 hypothetical phiSLT ORF110-like protein 23.29 ± 0.65
   SAUSA300_1942 hypothetical hypothetical protein 23.29 ± 11.27
   SAUSA300_0079 hypothetical putative lipoprotein 23.27 ± 6.02
   SAUSA300_1384 hypothetical phiSLT ORF100b-like protein, holin 23.25 ±
   6.98
   SAUSA300_1950 hypothetical hypothetical protein 23.24 ± 9.64
   SAUSA300_0320 gehB triacylglycerol lipase 23.13 ± 9.02
   SAUSA300_0370 hypothetical putative enterotoxin 23.06 ± 9.01
   SAUSA300_1224 hypothetical conserved hypothetical protein 22.85 ± 4.12
   SAUSA300_1925 hypothetical phiPVL ORF17-like protein 22.72 ± 9.85
   SAUSA300_1271 hypothetical hydrolase-like protein 22.57 ± 5.67
   SAUSA300_0547 sdrD sdrD protein 22.52 ± 1.23
   SAUSA300_0561 hypothetical hypothetical protein 22.37 ± 6.87
   SAUSA300_2367 hlgB gamma-hemolysin component B 22.27 ± 7.70
   SAUSA300_1671 hypothetical hypothetical protein 22.15 ± 10.08
   SAUSA300_2341 narJ respiratory nitrate reductase, subunit delta 22.11 ±
   4.50
   SAUSA300_0420 hypothetical hypothetical protein 22.10 ± 8.19
   SAUSA300_2281 hutG formimidoylglutamase 22.05 ± 12.63
   SAUSA300_1427 hypothetical phiSLT ORF86-like protein 21.94 ± 2.49
   SAUSA300_0691 saeR DNA-binding response regulator SaeR 21.93 ± 10.56
   SAUSA300_1519 hypothetical hypothetical protein 21.86 ± 0.84
   SAUSA300_0253 scdA cell wall biosynthesis protein ScdA 21.83 ± 12.24
   SAUSA300_2459 hypothetical MarR family transcriptional regulator 21.58
   ± 6.37
   SAUSA300_2505 hypothetical acetyltransferase 21.48 ± 5.28
   SAUSA300_0652 hypothetical hypothetical protein 21.46 ± 9.86
   SAUSA300_1213 hypothetical hypothetical protein 21.42 ± 8.18
   SAUSA300_1216 hypothetical cardiolipin synthetase 21.40 ± 13.46
   SAUSA300_0395 hypothetical superantigen-like protein 21.39 ± 9.28
   SAUSA300_1016 cyoE protoheme IX farnesyltransferase 21.38 ± 6.70
   SAUSA300_1126 rnc ribonuclease III 21.34 ± 5.04
   SAUSA300_1437 hypothetical phiSLT ORF204-like protein 21.26 ± 3.02
   SAUSA300_2145 hypothetical glycine betaine transporter 21.18 ± 9.85
   SAUSA300_2288 hypothetical ABC transporter ATP-binding protein 21.10 ±
   15.49
   SAUSA300_0698 pabA para-aminobenzoate synthase, glutamine
   amidotransferase, component II 21.05 ± 4.75
   SAUSA300_0519 hypothetical hypothetical protein 20.86 ± 6.93
   SAUSA300_2330 hypothetical hypothetical protein 20.82 ± 4.02
   SAUSA300_0141 deoB phosphopentomutase 20.69 ± 9.71
   SAUSA300_1684 hypothetical hypothetical protein 20.53 ± 11.18
   SAUSA300_1595 tgt queuine tRNA-ribosyltransferase 20.53 ± 9.07
   SAUSA300_0442 hypothetical hypothetical protein 20.45 ± 3.70
   SAUSA300_0744 lgt prolipoprotein diacylglyceryl transferase 20.44 ±
   5.61
   SAUSA300_1576 recD2 helicase, RecD/TraA family 20.41 ± 6.63
   SAUSA300_2088 luxS S-ribosylhomocysteinase 20.40 ± 2.33
   SAUSA300_0131 hypothetical putative Bacterial sugar transferase 20.28 ±
   13.49
   SAUSA300_0649 hypothetical hypothetical protein 20.23 ± 0.89
   SAUSA300_2550 nrdG anaerobic ribonucleotide reductase, small subunit
   20.22 ± 10.12
   SAUSA300_2168 hypothetical hypothetical protein 20.16 ± 4.12
   SAUSA300_2587 hypothetical accessory secretory protein Asp1 20.06 ±
   9.42
   SAUSA300_2548 hypothetical hypothetical protein 19.98 ± 7.37
   SAUSA300_1021 hypothetical hypothetical protein 19.92 ± 15.09
   SAUSA300_0456 rrlA 23S ribosomal RNA 19.91 ± 0.15
   SAUSA300_0431 hypothetical hypothetical protein 19.86 ± 4.23
   SAUSA300_1247 hypothetical conserved hypothetical protein 19.79 ± 10.23
   SAUSA300_2108 mtlD mannitol-1-phosphate 5-dehydrogenase 19.74 ± 9.18
   SAUSA300_2516 hypothetical short chain dehydrogenase/reductase family
   oxidoreductase 19.65 ± 10.14
   SAUSA300_0450 treR trehalose operon repressor 19.59 ± 13.38
   SAUSA300_0422 hypothetical hypothetical protein 19.54 ± 2.66
   SAUSA300_1739 hypothetical hypothetical protein 19.47 ± 8.56
   SAUSA300_0257 lrgB antiholin-like protein LrgB 19.47 ± 17.61
   SAUSA300_0056 hypothetical hypothetical protein 19.05 ± 4.22
   SAUSA300_2352 hypothetical addiction module antitoxin 18.95 ± 11.82
   SAUSA300_2236 hypothetical hypothetical protein 18.82 ± 4.26
   SAUSA300_1409 hypothetical hypothetical protein 18.77 ± 11.78
   SAUSA300_1304 hypothetical hypothetical protein 18.73 ± 5.92
   SAUSA300_1934 hypothetical phi77 ORF020-like protein, phage major tail
   protein 18.68 ± 3.51
   SAUSA300_1279 phoU phosphate transport system regulatory protein PhoU
   18.68 ± 7.74
   SAUSA300_1217 hypothetical ABC transporter ATP-binding protein 18.66 ±
   8.42
   SAUSA300_0468 hypothetical TatD family hydrolase 18.62 ± 0.90
   SAUSA300_2132 hypothetical hypothetical protein 18.54 ± 17.28
   SAUSA300_0288 essD/esaD hypothetical protein 18.50 ± 12.03
   SAUSA300_2461 hypothetical glyoxalase family protein 18.38 ± 6.48
   SAUSA300_1349 bshA glycosyl transferase, group 1 family protein 18.26 ±
   11.03
   SAUSA300_1009 typA GTP-binding protein 18.22 ± 6.42
   SAUSA300_1755 splD serine protease SplD 18.20 ± 6.01
   SAUSA300_1966 hypothetical phi77 ORF014-like protein, phage
   anti-repressor protein 18.04 ± 5.61
   SAUSA300_1307 arlS sensor histidine kinase protein 18.01 ± 7.14
   SAUSA300_1918 hlb truncated beta-hemolysin 17.91 ± 11.34
   SAUSA300_1569 hypothetical U32 family peptidase 17.90 ± 6.37
   SAUSA300_1397 hypothetical phiSLT ORF213-like protein, major tail
   protein 17.88 ± 16.40
   SAUSA300_1032 hypothetical putative iron compound ABC transporter iron
   compound-binding protein 17.87 ± 9.01
   SAUSA300_0259 hypothetical PTS system, IIA component 17.72 ± 4.08
   SAUSA300_1070 hypothetical hypothetical protein 17.66 ± 6.61
   SAUSA300_1474 hypothetical hypothetical protein 17.57 ± 3.84
   SAUSA300_1451 hypothetical short chain dehydrogenase/reductase family
   oxidoreductase 17.47 ± 4.46
   SAUSA300_0769 hypothetical hypothetical protein 17.42 ± 7.43
   SAUSA300_2098 arsR ArsR family transcriptional regulator 17.36 ± 8.42
   SAUSA300_0094 hypothetical hypothetical protein 17.32 ± 9.77
   SAUSA300_1470 ispA geranyltranstransferase 17.29 ± 13.19
   SAUSA300_1403 hypothetical phiSLT ORF412-like protein, portal protein
   17.28 ± 10.80
   SAUSA300_2432 hypothetical MutT/NUDIX family hydrolase 17.26 ± 15.82
   SAUSA300_0631 hypothetical putative nucleoside transporter 17.25 ±
   11.20
   SAUSA300_1000 potB spermidine/putrescine ABC transporter permease 17.14
   ± 5.86
   SAUSA300_2559 hypothetical DNA-binding response regulator 17.10 ± 8.85
   SAUSA300_2467 srtA sortase 17.01 ± 6.72
   SAUSA300_2300 hypothetical transcriptional regulator, TetR family 16.92
   ± 5.04
   SAUSA300_0916 hypothetical hypothetical protein 16.89 ± 2.85
   SAUSA300_1444 scpB segregation and condensation protein B 16.85 ± 6.40
   SAUSA300_0995 hypothetical branched-chain alpha-keto acid dehydrogenase
   subunit E2 16.83 ± 18.68
   SAUSA300_0419 hypothetical tandem lipoprotein 16.78 ± 3.58
   SAUSA300_1563 accC acetyl-CoA carboxylase, biotin carboxylase 16.73 ±
   11.04
   SAUSA300_2027 alr alanine racemase 16.70 ± 16.05
   SAUSA300_2607 hisA
   phoribosyl)-5-((5-phosphoribosylamino)methylideneamino)
   imidazole-4-carboxamide 16.70 ± 11.46
   SAUSA300_0023 hypothetical hypothetical protein 16.69 ± 16.09
   SAUSA300_1622 tig trigger factor 16.44 ± 5.67
   SAUSA300_0011 hypothetical hypothetical protein 16.37 ± 4.02
   SAUSA300_1097 pyrF orotidine 5′-phosphate decarboxylase 16.34 ± 8.94
   SAUSA300_1339 hypothetical hypothetical protein 16.25 ± 5.49
   SAUSA300_0585 hypothetical hypothetical protein 16.24 ± 13.38
   SAUSA300_0839 nfu hypothetical protein 16.23 ± 12.30
   SAUSA300_0071 hypothetical ISSep1-like transposase 16.19 ± 3.17
   SAUSA300_0651 hypothetical CHAP domain-contain protein 16.09 ± 6.91
   SAUSA300_1599 hypothetical hypothetical protein 16.02 ± 7.75
   SAUSA300_1607 hypothetical hypothetical protein 16.02 ± 8.76
   SAUSA300_0588 hypothetical hypothetical protein 15.86 ± 15.72
   SAUSA300_2276 hypothetical peptidase, M20/M25/M40 family 15.84 ± 1.33
   SAUSA300_2055 murA UDP-N-acetylglucosamine 1-carboxyvinyltransferase
   15.79 ± 10.49
   SAUSA300_0808 hypothetical hypothetical protein 15.69 ± 12.88
   SAUSA300_0759 gpmI phosphoglyceromutase 15.68 ± 9.84
   SAUSA300_0857 ppiB hypothetical protein 15.66 ± 4.76
   SAUSA300_1051 hypothetical hypothetical protein 15.51 ± 14.05
   SAUSA300_1383 hypothetical phiSLT ORF484-like protein, lysin 15.46 ±
   15.13
   SAUSA300_1566 hypothetical hypothetical protein 15.42 ± 14.25
   SAUSA300_2040 hypothetical hypothetical protein 15.42 ± 12.63
   SAUSA300_1145 xerC tyrosine recombinase xerC 15.33 ± 4.57
   SAUSA300_0687 hypothetical putative hemolysin 15.14 ± 12.23
   SAUSA300_0630 hypothetical ABC transporter ATP-binding protein 15.07 ±
   10.45
   SAUSA300_1577 hypothetical TPR domain-containing protein 14.93 ± 1.75
   SAUSA300_1288 dapA dihydrodipicolinate synthase 14.75 ± 7.53
   SAUSA300_1937 hypothetical phi77 ORF045-like protein 14.69 ± 8.83
   SAUSA300_1419 hypothetical phiSLT ORF80-like protein 14.65 ± 9.06
   SAUSA300_2345 nirD nitrite reductase (NAD(P)H), small subunit 14.54 ±
   4.64
   SAUSA300_1365 rpsA 30S ribosomal protein S1 14.53 ± 3.46
   SAUSA300_0029 hypothetical hypothetical protein 14.39 ± 3.30
   SAUSA300_2575 hypothetical BglG family transcriptional antiterminator
   14.12 ± 4.67
   SAUSA300_1497 hypothetical glycine dehydrogenase subunit 1 14.08 ± 4.09
   SAUSA300_1682 ccpA catabolite control protein A 14.04 ± 8.43
   SAUSA300_0657 hypothetical hypothetical protein 14.02 ± 7.45
   SAUSA300_1955 hypothetical putative endodeoxyribonuclease RusA 13.92 ±
   10.12
   SAUSA300_0924 ktrD sodium transport family protein 13.85 ± 14.78
   SAUSA300_0077 hypothetical ABC transporter ATP-binding protein 13.80 ±
   6.67
   SAUSA300_0504 pdxS pyridoxal biosynthesis lyase PdxS 13.58 ± 7.70
   SAUSA300_0195 hypothetical transcriptional regulator 13.06 ± 13.37
   SAUSA300_1308 arlR DNA-binding response regulator 13.05 ± 5.02
   SAUSA300_0859 hypothetical NADH-dependent flavin oxidoreductase 12.99 ±
   7.37
   SAUSA300_1721 hypothetical hypothetical protein 12.97 ± 3.93
   SAUSA300_0186 argC N-acetyl-gamma-glutamyl-phosphate reductase 12.92 ±
   16.00
   SAUSA300_2641 hypothetical hypothetical protein 12.90 ± 8.36
   SAUSA300_0987 hypothetical cytochrome D ubiquinol oxidase, subunit II
   12.85 ± 10.22
   SAUSA300_1696 dat D-alanine aminotransferase 12.74 ± 5.48
   SAUSA300_1283 hypothetical phosphate ABC transporter, phosphate-binding
   protein PstS 12.73 ± 9.23
   SAUSA300_1185 miaB (dimethylallyl)adenosine tRNA methylthiotransferase
   12.62 ± 10.40
   SAUSA300_2365 hlgA gamma-hemolysin component A 12.56 ± 10.54
   SAUSA300_1394 hypothetical hypothetical protein 12.34 ± 12.26
   SAUSA300_0115 sirC iron compound ABC transporter permease SirC 12.30 ±
   6.17
   SAUSA300_2284 hypothetical hypothetical protein 12.20 ± 10.36
   SAUSA300_2225 moaC molybdenum cofactor biosynthesis protein MoaC 12.08
   ± 9.05
   SAUSA300_0244 hypothetical zinc-binding dehydrogenase family
   oxidoreductase 12.05 ± 9.79
   SAUSA300_2022 rpoF RNA polymerase sigma factor SigB 12.05 ± 6.83
   SAUSA300_1089 lspA lipoprotein signal peptidase 11.97 ± 6.81
   SAUSA300_1618 hemX hemA concentration negative effector hemX 11.88 ±
   1.05
   SAUSA300_0117 sirA iron compound ABC transporter iron compound-binding
   protein SirA 11.83 ± 7.84
   SAUSA300_0899 mecA adaptor protein 11.58 ± 10.37
   SAUSA300_2492 hypothetical acetyltransferase family protein 11.55 ±
   7.80
   SAUSA300_1433 hypothetical putative phage regulatory protein 11.41 ±
   8.17
   SAUSA300_1244 mscL large conductance mechanosensitive channel protein
   11.32 ± 7.21
   SAUSA300_0049 hypothetical hypothetical protein 11.30 ± 0.62
   SAUSA300_1667 hypothetical putative glycerophosphoryl diester
   phosphodiesterase 11.30 ± 7.51
   SAUSA300_0994 pdhB pyruvate dehydrogenase E1 component, beta subunit
   11.20 ± 8.12
   SAUSA300_0974 purN phosphoribosylglycinamide formyltransferase 11.07 ±
   8.08
   SAUSA300_0067 hypothetical universal stress protein 11.02 ± 9.02
   SAUSA300_1590 rsh (relA) GTP pyrophosphokinase 10.95 ± 7.18
   SAUSA300_0526 hypothetical methyltransferase small subunit 10.80 ±
   10.78
   SAUSA300_0952 hypothetical aminotransferase, class I 10.57 ± 6.79
   SAUSA300_1694 trmB tRNA (guanine-N(7)-)-methyltransferase 10.55 ± 16.08
   SAUSA300_0041 hypothetical hypothetical protein 10.41 ± 2.09
   SAUSA300_1449 hypothetical MutT/nudix family protein 10.11 ± 13.24
   SAUSA300_0724 hypothetical hypothetical protein 10.06 ± 2.60
   SAUSA300_1757 splB serine protease SplB 9.41 ± 4.17
   SAUSA300_0476 hypothetical hypothetical protein 9.18 ± 8.05
   SAUSA300_2052 hypothetical single-stranded DNA- binding protein family
   9.11 ± 18.19
   SAUSA300_2176 cbiO cobalt transporter ATP-binding subunit 9.03 ± 9.11
   SAUSA300_1112 stp1 protein phosphatase 2C domain-containing protein
   8.98 ± 14.19
   SAUSA300_0789 hypothetical putative thioredoxin 8.89 ± 18.33
   SAUSA300_0379 ahpF alkyl hydroperoxide reductase subunit F 8.46 ± 4.49
   SAUSA300_0348 tatA twin arginine-targeting protein translocase 8.36 ±
   5.53
   SAUSA300_0469 rnmV hypothetical protein 8.35 ± 0.35
   SAUSA300_1792 hypothetical hypothetical protein 8.20 ± 4.58
   SAUSA300_2061 atpH F0F1 ATP synthase subunit delta 7.98 ± 1.29
   SAUSA300_1092 pyrP uracil permease 7.85 ± 2.60
   SAUSA300_0905 hypothetical hypothetical protein 7.61 ± 3.76
   SAUSA300_0444 gltC LysR family regulatory protein 7.59 ± 2.70
   SAUSA300_2646 trmE tRNA modification GTPase TrmE 7.41 ± 8.81
   SAUSA300_2105 mtlF PTS system, mannitol specific IIBC component 6.95 ±
   0.84
   SAUSA300_2486 clpL putative ATP-dependent Clp proteinase 6.73 ± 0.02
   SAUSA300_1887 pcrB geranylgeranylglyceryl phosphate synthase-like
   protein 6.58 ± 3.46
   SAUSA300_1653 hypothetical metal-dependent hydrolase 6.25 ± 8.63
   SAUSA300_2393 opuCa glycine betaine/carnitine/choline ABC transporter
   ATP-binding protein 6.25 ± 7.87
   SAUSA300_1183 hypothetical 2-oxoglutarate ferredoxin oxidoreductase
   subunit beta 6.19 ± 1.88
   SAUSA300_0393 hypothetical hypothetical protein 6.18 ± 2.30
   SAUSA300_0174 hypothetical hypothetical protein 6.15 ± 1.39
   SAUSA300_0841 hypothetical hypothetical protein 5.97 ± 2.99
   SAUSA300_1096 carB carbamoyl phosphate synthase large subunit 5.89 ±
   2.89
   SAUSA300_2593 hypothetical hypothetical protein 5.84 ± 3.04
   SAUSA300_0221 pflA pyruvate formate-lyase activating enzyme 5.68 ±
   18.96
   SAUSA300_0996 lpdA dihydrolipoamide dehydrogenase 5.49 ± 2.87
   SAUSA300_1992 agrA accessory gene regulator protein A 5.34 ± 14.81
   SAUSA300_1147 hslU ATP-dependent protease ATP-binding subunit HslU 4.99
   ± 6.72
   SAUSA300_1120 recG ATP-dependent DNA helicase RecG 4.60 ± 0.15
   SAUSA300_2078 murA UDP-N-acetylglucosamine 1-carboxyvinyltransferase
   3.18 ± 3.15
   SAUSA300_1583 cymR hypothetical protein 2.48 ± 0.46
   SAUSA300_0992 hypothetical hypothetical protein 2.24 ± 20.30
   SAUSA300_0634 fhuB ferrichrome transport permease fhuB 2.22 ± 4.57
   SAUSA300_0750 whiA hypothetical protein 1.88 ± 4.32
   SAUSA300_2485 hypothetical methylated DNA-protein cysteine
   methyltransferase 1.78 ± 9.18
   SAUSA300_0426 hypothetical hypothetical protein 0.95 ± 5.09
   SAUSA300_2598 capA capsular polysaccharide biosynthesis protein Cap1A
   0.85 ± 1.11
   SAUSA300_2246 hypothetical hypothetical protein 0.51 ± 16.59
   SAUSA300_2518 hypothetical hydrolase family protein 0.42 ± 7.59
   SAUSA300_0355 hypothetical acetyl-CoA acetyltransferase −0.68 ^a ± 4.44
   SAUSA300_0398 hypothetical superantigen-like protein −0.83 ^a ± 2.42
   SAUSA300_2226 moaB molybdenum cofactor biosynthesis protein B −1.15 ^a
   ± 5.09
   SAUSA300_0945 hypothetical isochorismate synthase family protein −1.17
   ^a ± 14.05
   SAUSA300_0904 yjbI hypothetical protein −1.32 ^a ± 9.61
   SAUSA300_0423 hypothetical hypothetical protein −2.20 ^a ± 9.08
   SAUSA300_1422 hypothetical phiSLT ORF65-like protein −2.77 ^a ± 6.35
   SAUSA300_0068 hypothetical cadmium-exporting ATPase, truncation −2.79
   ^a ± 8.85
   SAUSA300_1870 hypothetical hypothetical protein −2.92 ^a ± 15.58
   SAUSA300_1139 sucD succinyl-CoA synthetase subunit alpha −2.94 ^a ±
   8.32
   SAUSA300_0918 ugtP diacylglycerol glucosyltransferase −3.09 ^a ± 8.63
   SAUSA300_0597 hypothetical putative endonuclease III −3.15 ^a ± 14.78
   SAUSA300_0326 hypothetical hypothetical protein −3.64 ^a ± 2.40
   SAUSA300_0690 saeS sensor histidine kinase SaeS −4.88 ^a ± 14.01
   SAUSA300_0560 vraB acetyl-CoA c-acetyltransferase −5.06 ^a ± 6.53
   SAUSA300_2334 hypothetical hypothetical protein -5.12 ^a ± 7.55
   SAUSA300_2025 rsbU sigma-B regulation protein −5.19 ^a ± 6.08
   SAUSA300_2152 lacD tagatose 1,6-diphosphate aldolase −5.59 ^a ± 11.59
   SAUSA300_1680 acuA acetoin utilization protein AcuA −5.94 ^a ± 10.87
   SAUSA300_2024 rsbV anti-sigma-B factor, antagonist −6.77 ^a ± 14.71
   SAUSA300_0618 mntC ABC transporter substrate-binding protein −6.85 ^a ±
   4.61
   SAUSA300_1876 hypothetical DNA polymerase IV −6.91 ^a ± 9.59
   SAUSA300_1465 hypothetical 2-oxoisovalerate dehydrogenase, E1
   component, beta subunit −7.15 ^a ± 6.73
   SAUSA300_1573 hypothetical Holliday junction resolvase-like protein
   −10.10 ^a ± 6.88
   SAUSA300_1473 nusB transcription antitermination protein NusB −10.84 ^a
   ± 10.00
   SAUSA300_1357 aroC chorismate synthase −11.88 ^a ± 0.89
   SAUSA300_1095 carA carbamoyl phosphate synthase small subunit −14.12 ^a
   ± 10.52
   SAUSA300_1469 argR arginine repressor −14.16 ^a ± 8.61
   SAUSA300_1615 hemB delta-aminolevulinic acid dehydratase −14.95 ^a ±
   14.12
   SAUSA300_1467 lpdA dihydrolipoamide dehydrogenase −15.68 ^a ± 14.07
   SAUSA300_0993 pdhA pyruvate dehydrogenase E1 component, alpha subunit
   −17.05 ^a ± 10.66
   SAUSA300_0752 clpP ATP-dependent Clp protease proteolytic subunit
   −17.66 ^a ± 11.34
   SAUSA300_1715 ribD riboflavin biosynthesis protein −23.78 ^a ± 4.28
   [55]Open in a new tab

   ^a EC damage below zero is due to the A[560nm] value of the mutant was
   higher than the A[560nm] of the negative control.

Table 2.

   Mutants significantly increase HMEC-1 damage vs. JE2 WT strain (EC
   damage rate ≥ 60%).
   Locus Gene Name Description % EC Damage (Mean ± SD)
   SAUSA300_1197 ND ^a glutathione peroxidase 62.86 ± 5.67
   SAUSA300_1333 hypothetical conserved hypothetical protein 62.17 ± 3.05
   SAUSA300_1485 hypothetical conserved hypothetical protein 61.86 ± 6.12
   SAUSA300_2221 moaD molybdopterin converting factor, subunit 1 61.64 ±
   3.61
   SAUSA300_0206 azoR flavodoxin family protein 60.82 ± 6.24
   SAUSA300_0335 mepA MATE efflux family protein 60.15 ± 8.13
   [56]Open in a new tab

   ^a ND: not determined.

Table 3.

   Verification of EC damage of JE WT strain and selected mutants using
   24-well plates assay.
   Locus Group Gene Name % EC Damage (Mean ± SD)
   384-Well Plates 24-Well Plates
   JE2 Wildtype 46.19 ± 2.97 42.43 ± 6.44
   SAUSA300_1197 EC damage ≥ 60%
   in 384-well plates hypothetical 62.86 ± 5.67 59.40 ± 1.50
   SAUSA300_1333 hypothetical 62.17 ± 3.05 66.92 ± 0.84
   SAUSA300_1485 hypothetical 61.86 ± 6.12 61.75 ^a
   SAUSA300_2221 moaD 61.64 ± 3.61 59.90 ± 1.08
   SAUSA300_0206 hypothetical 60.82 ± 6.24 69.33 ± 0.48
   SAUSA300_0335 hypothetical 60.15 ± 8.31 63.35 ± 2.06
   SAUSA300_1040 EC damage ≤ 30%
   in 384-well plates hypothetical 26.74 ± 8.21 30.92 ^a
   SAUSA300_1875 hypothetical 24.52 ± 10.68 30.51 ^a
   SAUSA300_0871 hypothetical 24.49 ± 12.19 28.60 ^a
   SAUSA300_1950 hypothetical 23.24 ± 9.64 25.87 ^a
   SAUSA300_0253 scdA 21.83 ± 12.24 22.52 ^a
   SAUSA300_0649 hypothetical 20.24 ± 0.89 22.65 ^a
   SAUSA300_2587 hypothetical 20.06 ± 9.42 26.45 ^a
   SAUSA300_0631 hypothetical 17.25 ± 11.20 23.00 ^a
   SAUSA300_2027 alr 16.70 ± 16.05 3.28 ± 1.38
   SAUSA300_2055 murA 15.79 ± 10.49 7.62 ± 0.59
   SAUSA300_1682 ccpA 14.04 ± 8.43 13.43 ^a
   SAUSA300_1696 dat 12.74 ± 5.48 14.99 ± 1.34
   SAUSA300_0974 purN 11.07 ± 8.08 20.58 ^a
   SAUSA300_1563 accC 16.73 ± 11.04 11.82 ± 0.72
   SAUSA300_0041 hypothetical 10.41 ± 2.09 3.30 ^a
   SAUSA300_0994 pdhB 11.20 ± 8.12 19.36 ^a
   SAUSA300_0186 argC 12.92 ± 16.00 15.20 ± 2.13
   SAUSA300_1992 agrA 5.34 ± 14.81 −3.82 ± 1.77
   SAUSA300_0355 hypothetical −0.68 ± 4.44 −1.20 ^a
   SAUSA300_0690 saeS −4.89 ± 14.01 −12.80 ± 1.77
   [57]Open in a new tab

   ^a Verification of these mutants was performed once using the 24-well
   plates assay.

Table 4.

   Numbers of genes from different KEGG pathway categories.
   Categories Sub-Groups No. of Mutants with
   Decreased HMEC-1
   Damage No. of Mutants with
   Increased HMEC-1
   Damage
   Metabolism Carbohydrate metabolism 53
   Amino acid metabolism 33
   Metabolism of cofactors and vitamins 11
   Lipid metabolism 8 1
   Nucleotide metabolism 8
   Biosynthesis of other secondary metabolites 7
   Energy metabolism 7
   Metabolism of other amino acids 3 1
   Metabolism of terpenoids and polyketides 3
   Glycan biosynthesis and metabolism 2
   Xenobiotics biodegradation and metabolism 1
   Genetic information processing Homologous recombination 4
   DNA replication 2
   Mismatch repair 2
   Protein export 2
   Ribosome 2
   Sulfur relay system 2 1
   RNA degradation 1
   Environmental information processing Two-component system 13
   ABC transporters 9
   Other 3
   Cellular processes Quorum sensing 9
   Total 185 3
   [58]Open in a new tab

Figure 2.

   [59]Figure 2
   [60]Open in a new tab

   Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of
   the mutant strains significantly decreasing HMEC-1 damage rate: (A)
   genes were identified in the KEGG database and belonged to four major
   KEGG pathways; (B) the sub-pathway enrichment analysis of the genes in
   the metabolism pathway; and (C) the sub-pathway enrichment analysis of
   the genes in the other three pathways.

3. Discussion

   It is well recognized that EC damage plays a crucial role in the
   pathogenesis of S. aureus endovascular infection [[61]5,[62]13,[63]14].
   For instance, we have demonstrated a positive correlation between in
   vitro EC damage and virulence, as well as antibiotic treatment
   persistent outcome in an experimental endocarditis model caused by
   clinical MRSA isolates [[64]5]. In addition, we also noticed that
   clinical MRSA strains collected from patients with persistent
   bacteremia cause significantly greater EC damage compared to clinical
   resolving MRSA isolates [[65]15]. Moreover, the inactivation of agr,
   saeR, and arlSR has been proved significantly reduce EC damage as
   compared to their respective parental strains [[66]13,[67]16]. However,
   these studies only focused on a few virulence factors in S. aureus.
   Thus, the current study was designed to broadly define genetic
   determiners in S. aureus which involve in human EC damage using a
   high-throughput approach to screen a transposon mutant library
   containing 1920 non-essential gene mutants in MRSA USA300 JE2
   background.

   In the current study, we first verified the reliability of our
   high-throughput screening system. Consistent with previous reports
   [[68]13,[69]16], we demonstrated that the inactivation of global
   regulators such as agr, arlRS, or saeRS significantly decreases EC
   damage. In addition, consistent results were obtained between 384-well
   and 24-well plates assays, which validated the improvement of testing
   significantly more samples each time.

   Several interesting and important observations emerged from the present
   investigations. Overall, over 320 mutants had a significant impact on
   the EC damage. The majority of these mutants significantly reduced EC
   damage vs. JE2 parental strain. Using KEGG pathway analysis, mutant
   strains were classified into four categories, including metabolism,
   genetic information processing, environmental information processing,
   and cellular processes ([70]Figure 3). Only six mutants were found with
   significantly increased EC damage vs. JE2 parental strain. Importantly,
   many of these genes are not previously defined to impact human EC
   damage in S. aureus.

Figure 3.

   [71]Figure 3
   [72]Open in a new tab

   Genetic factors in MRSA JE2 strain contribute to the HMEC-1 damage by
   KEGG analysis. These factors may ultimately impact the pathogenesis and
   treatment outcome in MRSA endovascular infection.

   Many staphylococcal genetic factors related to metabolism were shown to
   intimately impact the EC damage. For instance, several gene mutants
   related to carbohydrate metabolism including tricarboxylic acid (TCA)
   cycle (e.g., pdhA, and lpdA) showed significantly decreased EC damage.
   Inactivation of pdhA or lpdA was reported to be associated with slower
   growth [[73]17,[74]18]. Since the TCA cycle processes produce the main
   energy resources for cellular activities [[75]19], inactivation of
   corresponding TCA genes may result in lack of energy which may
   subsequently cause slower growth and decrease EC damage. In addition,
   mutants with genes related to energy metabolism (e.g., cyoE, and atpH)
   also displayed lower EC damage rates vs. parental strain JE2. It has
   been reported that cyoE encoding a protoheme IX farnesyltransferase is
   essential for processing heme into the electron transport chain and
   plays a critical role in cytolytic toxins production in S. aureus.
   Deletion of cyoE in S. aureus significantly decreases the expression of
   cytolytic toxins [[76]20]. Turner et al. reported that mutation of aptH
   (associated with ATP synthase) had attenuated virulence and less
   invasiveness in vivo [[77]21]. These results suggest that genetic
   factors associated with energy metabolism have activities on EC damage
   that may link to virulence. Lipid metabolism genes (e.g., gehB, and
   ugtP) were reported to promote biofilm formation and host cell invasion
   [[78]22]. We found that the mutation of these genes had significantly
   decreased EC damage vs. JE2 parental strain. These results may indicate
   a connection between lipid metabolism and EC damage. Genetic factors
   associated with nucleotides metabolism (e.g., purN) were also found to
   positively impact the EC damage. purN encodes the enzyme in de novo
   purine biosynthesis pathway which generates ATP and GTP that can be
   processed to stringent response alarmone, guanosine
   3′-diphosphate-5-di(tri)phosphate ((p)ppGpp) [[79]15]. Increased GTP
   and subsequent (p)ppGpp levels lead to enhanced persistent bacteremia
   (PB) phenotypes including a higher EC damage rate [[80]15]. It is
   worthwhile to mention, genes related to staphylococcal cell-wall
   peptidoglycan biosynthesis (e.g., murA) and cell division (e.g., scdA)
   showed significant positive effects on EC damage. Cell-wall synthesis
   has long been considered an important target for novel anti-S. aureus
   agents [[81]23,[82]24], and our findings have implications for the
   approach.

   In the genetic information processing pathways, genes involved in
   homologous recombination (e.g., recD, and recG), ribosome (e.g., rrlA,
   and rpsA), and protein export (e.g., lspA, and tatA) were identified to
   affect EC damage. For example, the signal peptidase encoded by lspA is
   required for biogenesis of bacterial lipoproteins, and failure to
   produce mature lipoproteins has previously been shown to impair
   pathogenicity and immune-modulating [[83]25]. The results suggested
   that some genes related to genetic information processing also play a
   role in human EC damage.

   The inactivation of genes involved in environmental information
   processing pathways such as ABC transporter (e.g., fhuB, and mntC) and
   two-component system (e.g., saeSR, and arlSR) also decreased EC damage.
   These findings were in accordance with previous studies showing the
   presence of these gene products was associated with higher in vivo
   virulence potential vs. their respective WT strains
   [[84]13,[85]26,[86]27,[87]28].

   Genes involved in cellular process, specifically quorum sensing (e.g.,
   agr, and luxS), were identified to contribute to the EC damage. It is
   well known that quorum sensing via agr plays a central role in the
   pathogenesis of S. aureus. Under high cell density, agr is responsible
   for the increased expression of many toxins which may impact the EC
   damage [[88]16], while the function of luxS in S. aureus has not been
   well investigated.

   Genes unidentified in the KEGG pathways also showed a positive impact
   on the HMEC-1 damage in the current study. Some of these genes have
   been previously demonstrated to correlate with biofilm formation (e.g.,
   xerC), oxidative killing (e.g., nfu, and yjbI), hemolysis (e.g., hlb),
   and heat shock (e.g., hslU) [[89]29,[90]30,[91]31,[92]32]. In addition,
   few phage genes (SAUSA300_1433, SAUSA300_1934, SAUSA300_1936,
   SAUSA300_1968) were also shown impacts on the HMEC-1 damage.

   Mutants of six genes had elevated EC damage indicating their negative
   impact on the EC damage. Among these genes, mepA encodes a multidrug
   efflux pump protein [[93]33], azoR encodes quinone reductase [[94]34],
   moaD encodes one of the subunits of molydopterin synthase involved in
   sulfur relay system pathway [[95]35], gene SAUSA300_1197 encodes
   glutathione peroxidase. Further investigations related to the
   relationship between these genes and EC damage are needed.

4. Materials and Methods

4.1. Bacteria and Growth Conditions

   The strains used in the current study include MRSA JE2 (a plasmid-cured
   derivative of LAC USA300) and 1920 transposon non-essential gene
   mutants within the NTML [[96]6]. The NTML was kindly provided by the
   Network on Antimicrobial Resistance in Staphylococcus aureus (NARSA).
   The library was supplied in five 384-well microtiter plates. The plates
   containing MRSA mutant strains were duplicated and cultured in tryptic
   soy broth (TSB; Becton, Dickinson and Company, Franklin Lakes, NJ,
   USA). On the experiment day, bacterial strains were freshly inoculated
   in TSB media and cultured at 37 °C for 3 h to obtain logarithmic phase
   cells [[97]36], and adjusted to an OD[600nm] of 0.500 (~10^8 CFU/mL)
   and diluted accordingly. S. aureus inocula were confirmed by
   quantitative culture.

4.2. Endothelial Cell (HMEC-1) Culture

   The HMEC-1 cell line was obtained from Kathryn Kellar, of the Centers
   for Disease Control (CDC), in the U.S., and maintained as recommended
   [[98]10]. Primary cells were established from human dermal
   microvascular endothelial cells and immortalized by transfection with a
   Pbr322-based plasmid containing the coding region for the simian virus
   40 large T-antigen [[99]10].

4.3. HMEC-1 Damage Assay

   The effect of MRSA strains on EC damage was determined using a
   well-established 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium
   bromide (MTT) assay as described previously [[100]13,[101]37,[102]38].
   Briefly, logarithmic phase MRSA cells (1 × 10^5 CFU/well) were added to
   HMEC-1 cells in 384-well plates with a density of ~5 × 10^3 EC/well in
   MCDB131 medium to reach a multiplicity of infection (MOI) of 20, which
   JE2 parental caused ~50% HMEC-1 damage as established in our pilot
   experiments. After 3 hr invasion, extracellular MRSA cells were killed
   by adding lysostaphin (10 μg/mL) in full medium MCDB131 (Sigma-Aldrich,
   St. Louis, MO, USA) supplemented with 20% bovine calf serum, 2 mM
   glutamine, 100 IU/mL penicillin, and 100 mg/mL streptomycin
   [[103]13,[104]37]. At 18 hr incubation at 37 °C, MTT (5 mg/mL;
   Sigma-Aldrich, St. Louis, MO, USA) in Hank’s Balanced Salt Solution
   (HBSS, Thermo Fisher Scientific, Waltham, MA, USA) was added and
   incubated for 2 h, then the medium was replaced with 0.04 M HCl in
   absolute isopropanol (Thermo Fisher Scientific, Waltham, MA, USA) to
   stop the reaction and lyse the cells. Absorbance was measured at 560 nm
   (A[560nm]) using a microplate reader Synergy 2 (BioTek, Winooski, VT,
   USA). Uninfected HMEC-1 served as a negative control, and wells
   containing medium alone were used for background correction in each
   round. In addition, EC infected with ΔarlR in JE2 was selected as an
   additional control group as it was reported that arlSR inactivation
   leads to >70% reduction in human EC damage vs. JE2 parental strain
   [[105]13]. EC damage was calculated using the following formula: 1 −
   (A[560nm] of test well/A[560nm] of 0% − damage control well) as
   previously described [[106]37]. Each experiment was performed three
   times in triplicate.

4.4. Verification of the HMEC-1 Damage Screening Results

   After the screening of the whole library, JE2 WT strain and 20 randomly
   selected mutant strains with significantly decreased EC damage were
   confirmed again with the same MTT method using 24-well plates. In
   addition, the mutant strains with significantly increased EC damage
   were also tested in 24-well plates to confirm the damage results with
   the same method.

4.5. Statistical Analysis

   Statistical analysis was performed using GraphPad Prism 9 (GraphPad
   Software, Inc., San Diego, CA, USA). p-values were determined using the
   paired rank-sum test between mutant and JE2 wild-type strains. p < 0.05
   was considered statistically significant.

4.6. KEGG Enrichment Analysis

   The genes that caused a significant change in EC damage were classified
   using the Kyoto Encyclopedia of Genes and Genomes (KEGG) mapper tool
   with the mode of Staphylococcus aureus subsp. aureus USA300-FPR3757
   (saa) [[107]39]. The genes from different KEGG pathway categories were
   further analyzed.

5. Conclusions

   To our knowledge, the present study provides the first whole-genome
   screen to identify genetic factors that impact human EC damage in S.
   aureus. Importantly, we defined a set of staphylococcal genes, which
   are not previously known to be associated with EC damage, significantly
   contribute to this phenotype. Although these findings need to be
   further verified using mutation strains generated by gene deletion and
   complementation techniques, our results provide new insights into the
   relationship between genetic factors and EC damage in S. aureus. These
   genetic factors may be ideal targets for the development of effective
   therapeutic strategies to treat invasive MRSA endovascular infection.

Supplementary Materials

   The following supporting information can be downloaded at
   [108]https://www.mdpi.com/2079-6382/11/3/316/s1, Table S1: HMEC-1
   damage caused by all the mutant strains, except mutants presented in
   [109]Table 1 and [110]Table 2 in the NTML.
   [111]Click here for additional data file.^ (63.8KB, zip)

Author Contributions

   Y.Q.X. designed the study. X.X. and L.L. performed the experiments.
   Y.L., X.X. and Y.Q.X. performed data analysis and wrote the paper. All
   authors have read and agreed to the published version of the
   manuscript.

Funding

   This work was supported by the National Institutes of Health/National
   Institute of Allergy and Infectious Diseases grant R01AI139244 to
   Y.Q.X.

Institutional Review Board Statement

   Not applicable.

Informed Consent Statement

   Not applicable.

Data Availability Statement

   Not applicable.

Conflicts of Interest

   The authors declare no conflict of interest.

Footnotes

   Publisher’s Note: MDPI stays neutral with regard to jurisdictional
   claims in published maps and institutional affiliations.

References