Human immunodeficiency virus-specific gamma interferon enzyme-linked immunospot assay responses targeting specific regions of the proteome during primary subtype C infection are poor predictors of the course of viremia and set point

It is unknown whether patterns of human immunodeficiency virus (HIV)-specific T-cell responses during acute infection may influence the viral set point and the course of disease. We wished to establish whether the magnitude and breadth of HIV type 1 (HIV-1)-specific T-cell responses at 3 months postinfection were correlated with the viral-load set point at 12 months and hypothesized that the magnitude and breadth of HIV-specific T-cell responses during primary infection would predict the set point. Gamma interferon (IFN-γ) enzyme-linked immunospot (ELISPOT) assay responses across the complete proteome were measured in 47 subtype C HIV-1-infected participants at a median of 12 weeks postinfection. When corrected for amino acid length and individuals responding to each region, the order of recognition was as follows: Nef > Gag > Pol > Rev > Vpr > Env > Vpu > Vif > Tat. Nef responses were significantly (P < 0.05) dominant, targeted six epitopic regions, and were unrelated to the course of viremia. There was no significant difference in the magnitude and breadth of responses for each protein region with disease progression, although there was a trend of increased breadth (mean, four to seven pools) in rapid progressors. Correlation of the magnitude and breadth of IFN-γ responses with the viral set point at 12 months revealed almost zero association for each protein region. Taken together, these data demonstrate that the magnitude and breadth of IFN-γ ELISPOT assay responses at 3 months postinfection are unrelated to the course of disease in the first year of infection and are not associated with, and have low predictive power for, the viral set point at 12 months.     

The burden of common infectious disease syndromes at the clinic and household level from population-based surveillance in rural and urban Kenya

Background

Characterizing infectious disease burden in Africa is important for prioritizing and targeting limited resources for curative and preventive services and monitoring the impact of interventions.

Methods

From June 1, 2006 to May 31, 2008, we estimated rates of acute lower respiratory tract illness (ALRI), diarrhea and acute febrile illness (AFI) among >50,000 persons participating in population-based surveillance in impoverished, rural western Kenya (Asembo) and an informal settlement in Nairobi, Kenya (Kibera). Field workers visited households every two weeks, collecting recent illness information and performing limited exams. Participants could access free high-quality care in a designated referral clinic in each site. Incidence and longitudinal prevalence were calculated and compared using Poisson regression.

Results

Incidence rates resulting in clinic visitation were the following: ALRI — 0.36 and 0.51 episodes per year for children <5 years and 0.067 and 0.026 for persons ≥5 years in Asembo and Kibera, respectively; diarrhea — 0.40 and 0.71 episodes per year for children <5 years and 0.09 and 0.062 for persons ≥5 years in Asembo and Kibera, respectively; AFI — 0.17 and 0.09 episodes per year for children <5 years and 0.03 and 0.015 for persons ≥5 years in Asembo and Kibera, respectively. Annually, based on household visits, children <5 years in Asembo and Kibera had 60 and 27 cough days, 10 and 8 diarrhea days, and 37 and 11 fever days, respectively. Household-based rates were higher than clinic rates for diarrhea and AFI, this difference being several-fold greater in the rural than urban site.

Conclusions

Individuals in poor Kenyan communities still suffer from a high burden of infectious diseases, which likely hampers their development. Urban slum and rural disease incidence and clinic utilization are sufficiently disparate in Africa to warrant data from both settings for estimating burden and focusing interventions.     

Antioxidant Properties of the Major Polyphenolic Compounds in Broccoli

We have examined the antioxidant activity of the major phenolic compounds in Broccoli: two flavonol glycosides (quercetin 3-O-sophoroside and kaemp-ferol 3-O-sophoroside) and four hydroxycinnamic acid esters (1,2'-disinapoyl-2-feruloyl gentiobiose, 1-sinapoyl-2-feruloyl gentiobiose, 1,2,2'-trisinapoyl gentiobiose and 1,2-disinapoyl gentiobiose). The Trolox C equivalent antioxidant capacity (TEAC) and inhibition of iron/ascorbate-induced lipid per-oxidation of phosphatidyl choline vesicles were measured. In the aqueous phase TEAC assay, the two flavonol glycosides were less active than their respective aglycones. TEAC values for the hydroxycinnamic acid esters were less than the sum of their constituent hydroxycinnamic acids on a molar basis. Quercetin 3-O-sophoroside was a potent inhibitor of lipid peroxidation, in contrast to kaempferol 3-O-sophoroside. The hydroxycinnamic acid esters were highly effective at preventing lipid damage with the exception of 1,2,2'-trisinapoyl gentiobiose. The six compounds analysed herein demonstrate the antioxidant activity of the major phenolics in broccoli and indicate the effect on antioxidant activity of sugar substitutions in the phenolic B ring.     

Forest Fragmentation Reduces Seed Dispersal of Duckeodendron cestroides, a Central Amazon Endemic

Fragmentation that alters mutualistic relationships between plants and frugivorous animals may reduce the seed dispersal of trees. We examined the effects of forest fragmentation on the distributions of seeds and seedlings of a Central Amazon endemic tree, Duckeodendron cestroides . In the dry seasons of 2002–2004, seeds and first-year seedlings were counted within wedge-shaped transects centered around Duckeodendron adults in fragments and nearby continuous forests at the Biological Dynamics of Forest Fragmentation Project. Analyses showed that fragmentation reduced seed dispersal quantity and quality. The percent and distance of dispersed seeds were both twice as great in continuous forest as in fragments. The distances of each tree's five furthest dispersed seeds were three times greater in continuous forest than fragments. Over the 3-yr study, 20 times more seeds were dispersed more than 10 m from parent crowns in continuous forest than fragments. A regression analysis showed more dispersed seeds at all distances in continuous forest than fragments. Dispersal differences were strong in 2002 and 2004, years of large fruit crops, but weak or absent in 2003, when fruit production was low. As distance from parent crowns increased, the number of seedlings declined more rapidly in fragments than continuous forest. Distance-dependent mortality between the seed and seedling stages appeared to be more important in continuous forest than fragments. This research provides ample, indirect evidence demonstrating that forest fragmentation can result in the breakdown of a seed dispersal mutualism, potentially jeopardizing the reproduction of a rare, tropical tree.     

A yellow polysaccharide-producing bacterium with unusual characteristics

Summary A polysaccharide-producing Gram-negative bacterium was isolated from a sample of hay. It grew best on nitrate-containing media with sucrose as carbon source; the colony form was highly unusual. No polysaccharide was formed on glucose. A spontaneous mutant producing the same polysaccharide on both sucrose- and glucose-containing media was isolated. The polysaccharide has been characterized as an acid heteropolymer containing D-galacturonic acid, D-glucose, D-galactose and D-mannose in the approximate molar ratio 1:1:3:1, together with about 2 mol of acetate. The polysaccharide in aqueous solution was highly viscous with pseudoplastic characteristics.     

A Truncated Fragment of Src Protein Kinase Generated by Calpain-mediated Cleavage Is a Mediator of Neuronal Death in Excitotoxicity

Excitotoxicity resulting from overstimulation of glutamate receptors is a major cause of neuronal death in cerebral ischemic stroke. The overstimulated ionotropic glutamate receptors exert their neurotoxic effects in part by overactivation of calpains, which induce neuronal death by catalyzing limited proteolysis of specific cellular proteins. Here, we report that in cultured cortical neurons and in vivo in a rat model of focal ischemic stroke, the tyrosine kinase Src is cleaved by calpains at a site in the N-terminal unique domain. This generates a truncated Src fragment of ∼52 kDa, which we localized predominantly to the cytosol. A cell membrane-permeable fusion peptide derived from the unique domain of Src prevents calpain from cleaving Src in neurons and protects against excitotoxic neuronal death. To explore the role of the truncated Src fragment in neuronal death, we expressed a recombinant truncated Src fragment in cultured neurons and examined how it affects neuronal survival. Expression of this fragment, which lacks the myristoylation motif and unique domain, was sufficient to induce neuronal death. Furthermore, inactivation of the prosurvival kinase Akt is a key step in its neurotoxic signaling pathway. Because Src maintains neuronal survival, our results implicate calpain cleavage as a molecular switch converting Src from a promoter of cell survival to a mediator of neuronal death in excitotoxicity. Besides unveiling a new pathological action of Src, our discovery of the neurotoxic action of the truncated Src fragment suggests new therapeutic strategies with the potential to minimize brain damage in ischemic stroke.     

Process for the isolation of preparative quantities of

Pre-eclampsia (PE) is a serious complication of pregnancy with potentially life threatening consequences for both mother and baby. Presently there is no test with the required performance to predict which healthy first-time mothers will go on to develop PE. The high specificity, sensitivity, and multiplexed nature of selected reaction monitoring holds great potential as a tool for the verification and validation of putative candidate biomarkersfor disease states. Realization of this potential involves establishing a high throughput, cost effective, reproducible sample preparation workflow. We have developed a semi-automated HPLC-based sample preparation workflow before a label-free selected reaction monitoring approach. This workflow has been applied to the search for novel predictive biomarkers for PE.To discover novel candidate biomarkers for PE, we used isobaric tagging to identify several potential biomarker proteins in plasma obtained at 15 weeks gestation from nulliparous women who later developed PE compared with pregnant women who remained healthy. Such a study generates a number of “candidate” biomarkers that require further testing in larger patient cohorts. As proof-of-principle, two of these proteins were taken forward for verification in a 100 women (58 PE, 42 controls) using label-free SRM. We obtained reproducible protein quantitation across the 100 samples and demonstrated significant changes in protein levels, even with as little as 20% change in protein concentration. The SRM data correlated with a commercial ELISA, suggesting that this is a robust workflow suitable for rapid, affordable, label-free verification of which candidate biomarkers should be taken forward for thorough investigation. A subset of pregnancy-specific glycoproteins (PSGs) had value as novel predictive markers for PE.The identification of clinically relevant plasma biomarkers with diagnostic and/or predictive value continues to challenge the proteomics field. Whereas once the biomarker pipeline was described as a two part discovery and validation process, there is increasing consensus that an intermediate step is required in which the proteins identified in the discovery phase are technically verified in 50 to 200 samples. This verification step identifies false positives from the discovery phase and allows prioritization of proteins to be taken into large-scale clinical validation studies (1). Although commercial ELISA kits may be used in this phase, these are unavailable for many proteins, are expensive, and may lack specificity. In addition, sample requirements may be too high to perform ELISA on all candidates, especially if many proteins are identified as potential markers by low powered, high penetration discovery workflows.Selected reaction monitoring (SRM)¹ mass spectrometry has great potential as an alternative verification method (2–6) as it can be multiplexed, customized, and is highly specific. This potential has not been exploited to date, largely because of technical issues developing a low-cost, reproducible workflow encompassing plasma and serum preparation and LC/MS analysis with the capability to measure protein levels reproducible in hundreds of samples. With traditional stable isotope dilution SRM (SID-SRM), the high cost of accurately quantified, purified stable isotope encoded peptides or proteins may be prohibitive for the verification of multiple peptides from many proteins. Label-free relatively quantitative methods are increasingly popular in discovery proteomics but to a much lesser extent in targeted SRM studies (7, 8).For any SRM method, sample preparation workflows must balance the extent of enrichment and fractionation to enable quantification of lower abundance proteins, against increased technical variability (which is influenced by the number of sample handling steps) and reduced multiplexed potential as a consequence of fractionating peptides from the protein of interest into several distinct fractions. It is also essential that the true technical variation in the workflow is quantitatively evaluated from freezer to MS analysis, rather than just the variation within the LC-SRM part of the experiment. As a paradigm for a label-free SRM assay, we developed our workflow and applied it to the verification of candidate biomarkers that indicate the risk of pre-eclampsia (PE).PE affects 2–8% of pregnancies, and is characterized by hypertension and proteinuria, which may progress to severe maternal complications or death (9). Because delivery of the infant is the only effective intervention, a third of babies are born premature and fetal or newborn mortality is increased three- to 10-fold (10). Its complex etiology involves abnormal placentation, an altered immune response and a sensitized maternal vascular endothelium (11). Prediction of the condition in early pregnancy would allow prevention strategies, such as low dose aspirin, to be targeted to high risk women. In first-time pregnant women, a group particularly at risk, biomarkers continue to fall short of a test that would be useful or cost effective in clinical practice (12–14). Better-performing novel biomarkers are required.The aim of this study was to identify candidate predictive biomarkers for PE and then develop a verification assay using mass spectrometry to determine whether these should be taken forward into more extensive and expensive validation studies. Initial discovery experiments were employed using a pooled sample iTRAQ approach using two different MS platforms to increase plasma proteome coverage. Among the set of proteins discovered, we then developed a label-free SRM assay for relative quantification of CXCL7 (Platelet basic protein; PBP) and members of the Pregnancy specific glycoprotein (PSG) family in a 100-sample set from the international SCreeningfOr Pregnancy Endpoints (SCOPE) study (www.scopestudy.net). Our workflow allowed the specificity and linearity of response for each peptide to be determined, along with true technical variability. Although absolute concentration and LOD/LOQ cannot be calculated using this approach, we aimed to test the hypothesis that a label-free SRM approach could provide a rapid, robust, and efficient screen of candidate plasma biomarkers.     

A Label-free Selected Reaction Monitoring Workflow Identifies a Subset of Pregnancy Specific Glycoproteins as Potential Predictive Markers of Early-onset Pre-eclampsia

Pre-eclampsia (PE) is a serious complication of pregnancy with potentially life threatening consequences for both mother and baby. Presently there is no test with the required performance to predict which healthy first-time mothers will go on to develop PE. The high specificity, sensitivity, and multiplexed nature of selected reaction monitoring holds great potential as a tool for the verification and validation of putative candidate biomarkersfor disease states. Realization of this potential involves establishing a high throughput, cost effective, reproducible sample preparation workflow. We have developed a semi-automated HPLC-based sample preparation workflow before a label-free selected reaction monitoring approach. This workflow has been applied to the search for novel predictive biomarkers for PE.To discover novel candidate biomarkers for PE, we used isobaric tagging to identify several potential biomarker proteins in plasma obtained at 15 weeks gestation from nulliparous women who later developed PE compared with pregnant women who remained healthy. Such a study generates a number of “candidate” biomarkers that require further testing in larger patient cohorts. As proof-of-principle, two of these proteins were taken forward for verification in a 100 women (58 PE, 42 controls) using label-free SRM. We obtained reproducible protein quantitation across the 100 samples and demonstrated significant changes in protein levels, even with as little as 20% change in protein concentration. The SRM data correlated with a commercial ELISA, suggesting that this is a robust workflow suitable for rapid, affordable, label-free verification of which candidate biomarkers should be taken forward for thorough investigation. A subset of pregnancy-specific glycoproteins (PSGs) had value as novel predictive markers for PE.The identification of clinically relevant plasma biomarkers with diagnostic and/or predictive value continues to challenge the proteomics field. Whereas once the biomarker pipeline was described as a two part discovery and validation process, there is increasing consensus that an intermediate step is required in which the proteins identified in the discovery phase are technically verified in 50 to 200 samples. This verification step identifies false positives from the discovery phase and allows prioritization of proteins to be taken into large-scale clinical validation studies (1). Although commercial ELISA kits may be used in this phase, these are unavailable for many proteins, are expensive, and may lack specificity. In addition, sample requirements may be too high to perform ELISA on all candidates, especially if many proteins are identified as potential markers by low powered, high penetration discovery workflows.Selected reaction monitoring (SRM)¹ mass spectrometry has great potential as an alternative verification method (2–6) as it can be multiplexed, customized, and is highly specific. This potential has not been exploited to date, largely because of technical issues developing a low-cost, reproducible workflow encompassing plasma and serum preparation and LC/MS analysis with the capability to measure protein levels reproducible in hundreds of samples. With traditional stable isotope dilution SRM (SID-SRM), the high cost of accurately quantified, purified stable isotope encoded peptides or proteins may be prohibitive for the verification of multiple peptides from many proteins. Label-free relatively quantitative methods are increasingly popular in discovery proteomics but to a much lesser extent in targeted SRM studies (7, 8).For any SRM method, sample preparation workflows must balance the extent of enrichment and fractionation to enable quantification of lower abundance proteins, against increased technical variability (which is influenced by the number of sample handling steps) and reduced multiplexed potential as a consequence of fractionating peptides from the protein of interest into several distinct fractions. It is also essential that the true technical variation in the workflow is quantitatively evaluated from freezer to MS analysis, rather than just the variation within the LC-SRM part of the experiment. As a paradigm for a label-free SRM assay, we developed our workflow and applied it to the verification of candidate biomarkers that indicate the risk of pre-eclampsia (PE).PE affects 2–8% of pregnancies, and is characterized by hypertension and proteinuria, which may progress to severe maternal complications or death (9). Because delivery of the infant is the only effective intervention, a third of babies are born premature and fetal or newborn mortality is increased three- to 10-fold (10). Its complex etiology involves abnormal placentation, an altered immune response and a sensitized maternal vascular endothelium (11). Prediction of the condition in early pregnancy would allow prevention strategies, such as low dose aspirin, to be targeted to high risk women. In first-time pregnant women, a group particularly at risk, biomarkers continue to fall short of a test that would be useful or cost effective in clinical practice (12–14). Better-performing novel biomarkers are required.The aim of this study was to identify candidate predictive biomarkers for PE and then develop a verification assay using mass spectrometry to determine whether these should be taken forward into more extensive and expensive validation studies. Initial discovery experiments were employed using a pooled sample iTRAQ approach using two different MS platforms to increase plasma proteome coverage. Among the set of proteins discovered, we then developed a label-free SRM assay for relative quantification of CXCL7 (Platelet basic protein; PBP) and members of the Pregnancy specific glycoprotein (PSG) family in a 100-sample set from the international SCreeningfOr Pregnancy Endpoints (SCOPE) study (www.scopestudy.net). Our workflow allowed the specificity and linearity of response for each peptide to be determined, along with true technical variability. Although absolute concentration and LOD/LOQ cannot be calculated using this approach, we aimed to test the hypothesis that a label-free SRM approach could provide a rapid, robust, and efficient screen of candidate plasma biomarkers.