Untargeted metabolomic, and proteomic analysis identifies metabolic biomarkers and pathway alterations in individuals with 22q11.2 deletion syndrome.

INTRODUCTION: The chromosome 22q11.2 deletion syndrome (22q11.2DS) is characterized by a well-defined microdeletion and is associated with a wide range of brain-related phenotypes including schizophrenia spectrum disorders (SCZ), autism spectrum disorders (ASD), anxiety disorders and attention deficit disorders (ADHD). The typically deleted region in 22q11.2DS contains multiple genes which haploinsufficiency has the potential of altering the protein and the metabolic profiles. OBJECTIVES: Alteration in metabolic processes and downstream protein pathways during the early brain development may help to explain the increased prevalence of the observed neurodevelopmental phenotypes in 22q11.2DS. However, relatively little is known about the correlation of dysregulated protein/metabolite expression and neurobehavioral impairments in individuals who developed them over time. METHODS: In this study, we performed untargeted metabolic and proteomic analysis in plasma samples derived from 30 subjects including 16 participants with 22q11.2DS and 14 healthy controls (TD) enrolled in a longitudinal study, aiming to identify a metabolic and protein signature informing about the underlying mechanisms involved in disease development and progression. The metabolic and proteomic profiles were also compared between the participants with 22q11.2DS with and without various comorbidities, such as medical involvement, psychiatric conditions, and autism spectrum disorder (ASD) to detect potential changes among multiple specimens, collected overtime, with the aim to understand the basic underlying mechanisms involved in disease development and progression. RESULTS: We observed a large number of statistically significant differences in metabolites between the two groups. Among them, the levels of taurine and arachidonic acid were significantly lower in 22q11.2DS compared to the TD group. In addition, we identified 16 proteins that showed significant changes in expression levels (adjusted P < 0.05) in 22q11.2DS as compared to TD, including those involved in 70 pathways such as gene expression, the PI3K-Akt signaling pathway and the complement system. Within participants with 22q11.2DS, no significant changes in those with and without medical or psychiatric conditions were observed. CONCLUSION: To our knowledge, this is the first report on plasma metabolic and proteomic profiling and on the identification of unique biomarkers in 22q11.2DS. These findings may suggest the potential role of the identified metabolites and proteins as biomarkers for the onset of comorbid conditions in 22q11.2DS. Ultimately, the altered protein pathways in 22q11.2DS may provide insights of the biological mechanisms underlying the neurodevelopmental phenotype and may provide missing molecular outcome measures in future clinical trials to assess early-diagnosis treatment and the efficacy of response to targeted treatment.

Transcriptional drifts associated with environmental changes in endothelial cells.

Environmental cues, such as physical forces and heterotypic cell interactions play a critical role in cell function, yet their collective contributions to transcriptional changes are unclear. Focusing on human endothelial cells, we performed broad individual sample analysis to identify transcriptional drifts associated with environmental changes that were independent of genetic background. Global gene expression profiling by RNA sequencing and protein expression by liquid chromatography-mass spectrometry directed proteomics distinguished endothelial cells in vivo from genetically matched culture (in vitro) samples. Over 43% of the transcriptome was significantly changed by the in vitro environment. Subjecting cultured cells to long-term shear stress significantly rescued the expression of approximately 17% of genes. Inclusion of heterotypic interactions by co-culture of endothelial cells with smooth muscle cells normalized approximately 9% of the original in vivo signature. We also identified novel flow dependent genes, as well as genes that necessitate heterotypic cell interactions to mimic the in vivo transcriptome. Our findings highlight specific genes and pathways that rely on contextual information for adequate expression from those that are agnostic of such environmental cues.

A Multiomic Analysis of Chicken Serum Revealed the Modulation of Host Factors Due to Campylobacter jejuni Colonization and In-Water Supplementation of Eugenol Nanoemulsion.

Campylobacter jejuni is a foodborne pathogen that causes campylobacteriosis globally, affecting ~95 million people worldwide. Most C. jejuni infections involve consuming and/or handling improperly cooked poultry meat. To better understand chicken host factors modulated by Campylobacter colonization, we explored a novel LCMS-based multiomic technology using three experimental groups: (1) negative control, (2) positive control, and (3) eugenol nanoemulsion (EGNE) treatment (supplemented with 0.125% EGNE in the water) of broiler chickens (n = 10 birds/group). Birds in groups two and three were challenged with C. jejuni on day 7, and serum samples were collected from all groups on day 14. Using this multiomic analysis, we identified 1216 analytes (275 compounds, seven inorganics, 407 lipids, and 527 proteins). The colonization of C. jejuni significantly upregulated CREG1, creatinine, and 3-[2-(3-Hydroxyphenyl) ethyl]-5-methoxyphenol and downregulated sphingosine, SP d18:1, high mobility group protein B3, phosphatidylcholines (PC) P-20:0_16:0, PC 11:0_26:1, and PC 13:0_26:2. We found that 5-hydroxyindole-3-acetic acid significantly increased with the EGNE treatment when compared to the positive and negative controls. Additionally, the treatment increased several metabolites when compared to the negative controls. In conclusion, this study revealed several potential targets to control Campylobacter in broiler chickens.

Severe COVID-19 in pregnancy has a distinct serum profile, including greater complement activation and dysregulation of serum lipids.

BACKGROUND: Pregnancies complicated by Coronavirus Disease 2019 (COVID-19) are at an increased risk of severe morbidity due to physiologic changes in immunologic, cardiovascular, and respiratory function. There is little is known about how severity of COVID-19 changes protein and metabolite expression in pregnancy. OBJECTIVE: This study aims to investigate the pathophysiology behind various clinical trajectories in pregnant patients diagnosed with COVID-19 using multi-omics profiling. STUDY DESIGN: This is a prospective cohort study of 30 pregnant patients at a single tertiary care center. Participants were categorized by severity of COVID-19 disease (control, asymptomatic, mild/moderate, or severe). Maternal serum samples underwent LC-MS-based multiomics analysis for profiling of proteins, lipids, electrolytes, and metabolites. Linear regression models were used to assess how disease severity related to analyte levels. Reactome pathway enrichment analysis was conducted on differential analytes. RESULTS: Of 30 participants, 25 had confirmed diagnosis of COVID-19 (6 asymptomatic (one post-infection), 13 mild/moderate (all post-infection), 6 severe), and 5 participants were controls. Severe COVID-19 was associated with distinct profiles demonstrating significant proteomic and lipidomic signatures which were enriched for annotations related to complement and antibody activity. (FDR < 0.05). Downregulated analytes were not significantly enriched but consisted of annotation terms related to lipoprotein activity (FDR > 0.2). Post-infection mild/moderate COVID-19 did not have significantly altered serum protein, metabolite, or lipid metabolite levels compared to controls. CONCLUSIONS: Pregnancies with severe COVID-19 demonstrate greater inflammation and complement activation and dysregulation of serum lipids. This altered multiomic expression provides insight into the pathophysiology of severe COVID-19 in pregnancy and may serve as potential indicators for adverse pregnancy outcomes.

DNA methylation-based estimator of telomere length.

Telomere length (TL) is associated with several aging-related diseases. Here, we present a DNA methylation estimator of TL (DNAmTL) based on 140 CpGs. Leukocyte DNAmTL is applicable across the entire age spectrum and is more strongly associated with age than measured leukocyte TL (LTL) (r ~-0.75 for DNAmTL versus r ~ -0.35 for LTL). Leukocyte DNAmTL outperforms LTL in predicting: i) time-to-death (p=2.5E-20), ii) time-to-coronary heart disease (p=6.6E-5), iii) time-to-congestive heart failure (p=3.5E-6), and iv) association with smoking history (p=1.21E-17). These associations are further validated in large scale methylation data (n=10k samples) from the Framingham Heart Study, Women's Health Initiative, Jackson Heart Study, InChianti, Lothian Birth Cohorts, Twins UK, and Bogalusa Heart Study. Leukocyte DNAmTL is also associated with measures of physical fitness/functioning (p=0.029), age-at-menopause (p=0.039), dietary variables (omega 3, fish, vegetable intake), educational attainment (p=3.3E-8) and income (p=3.1E-5). Experiments in cultured somatic cells show that DNAmTL dynamics reflect in part cell replication rather than TL per se. DNAmTL is not only an epigenetic biomarker of replicative history of cells, but a useful marker of age-related pathologies that are associated with it.

DNA methylation GrimAge strongly predicts lifespan and healthspan.

It was unknown whether plasma protein levels can be estimated based on DNA methylation (DNAm) levels, and if so, how the resulting surrogates can be consolidated into a powerful predictor of lifespan. We present here, seven DNAm-based estimators of plasma proteins including those of plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. The resulting predictor of lifespan, DNAm GrimAge (in units of years), is a composite biomarker based on the seven DNAm surrogates and a DNAm-based estimator of smoking pack-years. Adjusting DNAm GrimAge for chronological age generated novel measure of epigenetic age acceleration, AgeAccelGrim.Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E-17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment.Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies.

Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies.

DNA methylation (DNAm)-based biomarkers of aging have been developed for many tissues and organs. However, these biomarkers have sub-optimal accuracy in fibroblasts and other cell types used in ex vivo studies. To address this challenge, we developed a novel and highly robust DNAm age estimator (based on 391 CpGs) for human fibroblasts, keratinocytes, buccal cells, endothelial cells, lymphoblastoid cells, skin, blood, and saliva samples. High age correlations can also be observed in sorted neurons, glia, brain, liver, and even bone samples. Gestational age correlates with DNAm age in cord blood. When used on fibroblasts from Hutchinson Gilford Progeria Syndrome patients, this age estimator (referred to as the skin & blood clock) uncovered an epigenetic age acceleration with a magnitude that is below the sensitivity levels of other DNAm-based biomarkers. Furthermore, this highly sensitive age estimator accurately tracked the dynamic aging of cells cultured ex vivo and revealed that their proliferation is accompanied by a steady increase in epigenetic age. The skin & blood clock predicts lifespan and it relates to many age-related conditions. Overall, this biomarker is expected to become useful for forensic applications (e.g. blood or buccal swabs) and for a quantitative ex vivo human cell aging assay.

An epigenetic biomarker of aging for lifespan and healthspan.

Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.

No reliable gene expression biomarkers of current or impending neurocognitive impairment in peripheral blood monocytes of persons living with HIV.

Events leading to and propagating neurocognitive impairment (NCI) in HIV-1-infected (HIV+) persons are largely mediated by peripheral blood monocytes. We previously identified expression levels of individual genes and gene networks in peripheral blood monocytes that correlated with neurocognitive functioning in HIV+ adults. Here, we expand upon those findings by examining if gene expression data at baseline is predictive of change in neurocognitive functioning 2 years later. We also attempt to validate the original findings in a new sample of HIV+ patients and determine if the findings are HIV specific by including HIV-uninfected (HIV-) participants as a comparison group. At two time points, messenger RNA (mRNA) was isolated from the monocytes of 123 HIV+ and 60 HIV- adults enrolled in the Multicenter AIDS Cohort Study and analyzed with the Illumina HT-12 v4 Expression BeadChip. All participants received baseline and follow-up neurocognitive testing 2 years after mRNA analysis. Data were analyzed using standard gene expression analysis and weighted gene co-expression network analysis with correction for multiple testing. Gene sets were analyzed for GO term enrichment. Only weak reproducibility of associations of single genes with neurocognitive functioning was observed, indicating that such measures are unreliable as biomarkers for HIV-related NCI; however, gene networks were generally preserved between time points and largely reproducible, suggesting that these may be more reliable. Several gene networks associated with variables related to HIV infection were found (e.g., MHC I antigen processing, TNF signaling, interferon gamma signaling, and antiviral defense); however, no significant associations were found for neurocognitive function. Furthermore, neither individual gene probes nor gene networks predicted later neurocognitive change. This study did not validate our previous findings and does not support the use of monocyte gene expression profiles as a biomarker for current or future HIV-associated neurocognitive impairment.

GWAS of epigenetic aging rates in blood reveals a critical role for TERT.

DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 individuals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) paradoxically confer higher IEAA (P < 2.7 × 10-11). Causal modeling indicates TERT-specific and independent effects on LTL and IEAA. Experimental hTERT-expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the epigenetic clock, in addition to its established role of compensating for cell replication-dependent telomere shortening.

Coffee consumption is associated with DNA methylation levels of human blood.

Beneficial health effects have been attributed to coffee consumption, but it is not yet known whether epigenetics may have a role in this process. Here we associate epigenome-wide DNA methylation levels to habitual coffee consumption from two studies with blood (2100 and 215 participants), and one with saliva samples (256 participants). Adjusting for age, gender, and blood cell composition, one CpG (cg21566642 near ALPPL2) surpassed genome-wide significance (P=3.7 × 10-10) and from among 10 additional CpGs significant at P≤5.0 × 10-6, six were located within 1500 bps of a transcriptional start site. Results for these 11 top-ranked CpGs remained significant after further adjusting for smoking. Also, methylation levels of another 135 CpGs were influenced by both coffee drinking and smoking (P≤1.0 × 10-7). Functional enrichment analysis suggested that coffee-associated CpGs were located near transcription factor binding (P=1.2 × 10-6) and protein kinase activity genes (P=2.9 × 10-5). Interestingly, when we stratified by menopausal hormone therapy (MHT), methylation differences with coffee consumption were observed only in women who never used MHT. We did not replicate any of the associations found in blood in our saliva samples, suggesting that coffee may affect DNA methylation levels in immune cells of the blood but not in saliva.

Epigenetic clock analysis of diet, exercise, education, and lifestyle factors.

Behavioral and lifestyle factors have been shown to relate to a number of health-related outcomes, yet there is a need for studies that examine their relationship to molecular aging rates. Toward this end, we use recent epigenetic biomarkers of age that have previously been shown to predict all-cause mortality, chronic conditions, and age-related functional decline. We analyze cross-sectional data from 4,173 postmenopausal female participants from the Women's Health Initiative, as well as 402 male and female participants from the Italian cohort study, Invecchiare nel Chianti.Extrinsic epigenetic age acceleration (EEAA) exhibits significant associations with fish intake (p=0.02), moderate alcohol consumption (p=0.01), education (p=3x10-5), BMI (p=0.01), and blood carotenoid levels (p=1x10-5)-an indicator of fruit and vegetable consumption, whereas intrinsic epigenetic age acceleration (IEAA) is associated with poultry intake (p=0.03) and BMI (p=0.05). Both EEAA and IEAA were also found to relate to indicators of metabolic syndrome, which appear to mediate their associations with BMI. Metformin-the first-line medication for the treatment of type 2 diabetes-does not delay epigenetic aging in this observational study. Finally, longitudinal data suggests that an increase in BMI is associated with increase in both EEAA and IEAA.Overall, the epigenetic age analysis of blood confirms the conventional wisdom regarding the benefits of eating a high plant diet with lean meats, moderate alcohol consumption, physical activity, and education, as well as the health risks of obesity and metabolic syndrome.

Menopause accelerates biological aging.

Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the "epigenetic clock"), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Women's Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinson's disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further.

Accelerated epigenetic aging in brain is associated with pre-mortem HIV-associated neurocognitive disorders.

HIV infection leads to age-related conditions in relatively young persons. HIV-associated neurocognitive disorders (HAND) are considered among the most prevalent of these conditions. To study the mechanisms underlying this disorder, researchers need an accurate method for measuring biological aging. Here, we apply a recently developed measure of biological aging, based on DNA methylation, to the study of biological aging in HIV+ brains. Retrospective analysis of tissue bank specimens and pre-mortem data was carried out. Fifty-eight HIV+ adults underwent a medical and neurocognitive evaluation within 1 year of death. DNA was obtained from occipital cortex and analyzed with the Illumina Infinium Human Methylation 450K platform. Biological age determined via the epigenetic clock was contrasted with chronological age to obtain a measure of age acceleration, which was then compared between those with HAND and neurocognitively normal individuals. The HAND and neurocognitively normal groups did not differ with regard to demographic, histologic, neuropathologic, or virologic variables. HAND was associated with accelerated aging relative to neurocognitively normal individuals, with average relative acceleration of 3.5 years. Age acceleration did not correlate with pre-mortem neurocognitive functioning or HAND severity. This is the first study to demonstrate that the epigenetic age of occipital cortex samples is associated with HAND status in HIV+ individuals pre-mortem. While these results suggest that the increased risk of a neurocognitive disorder due to HIV might be mediated by an epigenetic aging mechanism, future studies will be needed to validate the findings and dissect causal relationships and downstream effects.

Acceleration of age-associated methylation patterns in HIV-1-infected adults.

Patients with treated HIV-1-infection experience earlier occurrence of aging-associated diseases, raising speculation that HIV-1-infection, or antiretroviral treatment, may accelerate aging. We recently described an age-related co-methylation module comprised of hundreds of CpGs; however, it is unknown whether aging and HIV-1-infection exert negative health effects through similar, or disparate, mechanisms. We investigated whether HIV-1-infection would induce age-associated methylation changes. We evaluated DNA methylation levels at >450,000 CpG sites in peripheral blood mononuclear cells (PBMC) of young (20-35) and older (36-56) adults in two separate groups of participants. Each age group for each data set consisted of 12 HIV-1-infected and 12 age-matched HIV-1-uninfected samples for a total of 96 samples. The effects of age and HIV-1 infection on methylation at each CpG revealed a strong correlation of 0.49, p<1 x 10(-200) and 0.47, p<1 x 10(-200). Weighted gene correlation network analysis (WGCNA) identified 17 co-methylation modules; module 3 (ME3) was significantly correlated with age (cor=0.70) and HIV-1 status (cor=0.31). Older HIV-1+ individuals had a greater number of hypermethylated CpGs across ME3 (p=0.015). In a multivariate model, ME3 was significantly associated with age and HIV status (Data set 1: ßage=0.007088, p=2.08 x 10(-9); ßHIV=0.099574, p=0.0011; Data set 2: ßage=0.008762, p=1.27 x 10(-5); ßHIV=0.128649, p=0.0001). Using this model, we estimate that HIV-1 infection accelerates age-related methylation by approximately 13.7 years in data set 1 and 14.7 years in data set 2. The genes related to CpGs in ME3 are enriched for polycomb group target genes known to be involved in cell renewal and aging. The overlap between ME3 and an aging methylation module found in solid tissues is also highly significant (Fisher-exact p=5.6 x 10(-6), odds ratio=1.91). These data demonstrate that HIV-1 infection is associated with methylation patterns that are similar to age-associated patterns and suggest that general aging and HIV-1 related aging work through some common cellular and molecular mechanisms. These results are an important first step for finding potential therapeutic targets and novel clinical approaches to mitigate the detrimental effects of both HIV-1-infection and aging.

The metabolite α-ketoglutarate extends lifespan by inhibiting ATP synthase and TOR.

Metabolism and ageing are intimately linked. Compared with ad libitum feeding, dietary restriction consistently extends lifespan and delays age-related diseases in evolutionarily diverse organisms. Similar conditions of nutrient limitation and genetic or pharmacological perturbations of nutrient or energy metabolism also have longevity benefits. Recently, several metabolites have been identified that modulate ageing; however, the molecular mechanisms underlying this are largely undefined. Here we show that α-ketoglutarate (α-KG), a tricarboxylic acid cycle intermediate, extends the lifespan of adult Caenorhabditis elegans. ATP synthase subunit ß is identified as a novel binding protein of α-KG using a small-molecule target identification strategy termed drug affinity responsive target stability (DARTS). The ATP synthase, also known as complex V of the mitochondrial electron transport chain, is the main cellular energy-generating machinery and is highly conserved throughout evolution. Although complete loss of mitochondrial function is detrimental, partial suppression of the electron transport chain has been shown to extend C. elegans lifespan. We show that α-KG inhibits ATP synthase and, similar to ATP synthase knockdown, inhibition by α-KG leads to reduced ATP content, decreased oxygen consumption, and increased autophagy in both C. elegans and mammalian cells. We provide evidence that the lifespan increase by α-KG requires ATP synthase subunit ß and is dependent on target of rapamycin (TOR) downstream. Endogenous α-KG levels are increased on starvation and α-KG does not extend the lifespan of dietary-restricted animals, indicating that α-KG is a key metabolite that mediates longevity by dietary restriction. Our analyses uncover new molecular links between a common metabolite, a universal cellular energy generator and dietary restriction in the regulation of organismal lifespan, thus suggesting new strategies for the prevention and treatment of ageing and age-related diseases.

N-acetylglucosaminylation of serine-aspartate repeat proteins promotes Staphylococcus aureus bloodstream infection.

Staphylococcus aureus secretes products that convert host fibrinogen to fibrin and promote its agglutination with fibrin fibrils, thereby shielding bacteria from immune defenses. The agglutination reaction involves ClfA (clumping factor A), a surface protein with serine-aspartate (SD) repeats that captures fibrin fibrils and fibrinogen. Pathogenic staphylococci express several different SD proteins that are modified by two glycosyltransferases, SdgA and SdgB. Here, we characterized three genes of S. aureus, aggA, aggB (sdgA), and aggC (sdgB), and show that aggA and aggC contribute to staphylococcal agglutination with fibrin fibrils in human plasma. We demonstrate that aggB (sdgA) and aggC (sdgB) are involved in GlcNAc modification of the ClfA SD repeats. However, only sdgB is essential for GlcNAc modification, and an sdgB mutant is defective in the pathogenesis of sepsis in mice. Thus, GlcNAc modification of proteins promotes S. aureus replication in the bloodstream of mammalian hosts.