BackgroundThe interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.Methodology/Principal FindingsWe present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.Conclusions/SignificanceWe describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.
Certain cytokines that are produced in liver may act as growth factors to facilitate wound healing and, hence, may influence liver regeneration. However, this hypothesis has not been directly tested. To determine whether the cytokine response evoked by partial hepatectomy (PH) modulates the process of liver regeneration, adult male rats were injected intraperitoneally with either goat polyclonal antibodies to rat tumor necrosis factor (TNF; 15 micrograms/g body wt) or an equal amount of goat anti-rat immunoglobulin G 1 h before PH. Animals were killed at 12, 24, 48, or 72 h post-PH, 1 h after injection with [3H]thymidine. Serum TNF levels were measured with the L929 cytotoxicity assay, titers of antibody to TNF were determined by enzyme-linked immunoabsorbent assay, and interleukin-6 (IL-6) concentrations were measured by B9 cell bioassay. Liver regeneration was assessed by [3H]thymidine incorporation into hepatic DNA and by immunohistochemical evidence of proliferating cell nuclear antigen (PCNA) expression. Antibodies to TNF were detected in treated rats but not in controls. Titers were highest at 12 h and progressively fell. Although TNF was never detected in serum, treatment with anti-TNF pre-PH significantly inhibited increases in serum IL-6 concentration post-PH. Anti-TNF pretreatment also inhibited [3H]thymidine incorporation into DNA, as well as expression of PCNA by both hepatocytes and liver nonparenchymal cells. These data indicate that TNF positively modulates liver regeneration after PH.
SignificanceDuchenne muscular dystrophy (DMD) is a rare and devastating muscle disease caused by mutations in the X-linked DMD gene (which encodes the dystrophin protein). Serum biomarkers hold significant potential as objective phenotypic measures of DMD disease state, as well as potential measures of pharmacological effects of and response to therapeutic interventions. Here we describe a proteomics approach to determine serum levels of 1,125 proteins in 93 DMD patients and 45 controls. The study identified 44 biomarkers that differed significantly between patients and controls. These data are being made available to DMD researchers and clinicians to accelerate the search for new diagnostic, prognostic, and therapeutic approaches.
Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.
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