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Multidimensional proteomics analysis of amniotic fluid to provide insight into the mechanisms of idiopathic preterm birth.

Buhimschi IA, Zhao G, Rosenberg VA, Abdel-Razeq S, Thung S, Buhimschi CS - PLoS ONE (2008)

Bottom Line: Women displaying the Q-profile (mean+/-SD, gestational age: 25+/-4 weeks, n = 40) were more likely to deliver preterm despite expectant management in the context of intact membranes and normal amniotic fluid clinical results.Utilizing identification-centered proteomics techniques (fluorescence two-dimensional differential gel electrophoresis, robotic tryptic digestion and mass spectrometry) coupled with Protein ANalysis THrough Evolutionary Relationships (PANTHER) ontological classifications, we determined that in amniotic fluids with Q-profile the differentially expressed proteins are primarily involved in non-inflammatory biological processes such as protein metabolism, signal transduction and transport.The altered proteins may offer opportunities for therapeutical intervention and future drug development to prevent prematurity.

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven, Connecticut, United States of America. irina.buhimschi@yale.edu

ABSTRACT

Background: Though recent advancement in proteomics has provided a novel perspective on several distinct pathogenetic mechanisms leading to preterm birth (inflammation, bleeding), the etiology of most preterm births still remains elusive. We conducted a multidimensional proteomic analysis of the amniotic fluid to identify pathways related to preterm birth in the absence of inflammation or bleeding.

Methodology/principal findings: A proteomic fingerprint was generated from fresh amniotic fluid using surface-enhanced laser desorbtion ionization time of flight (SELDI-TOF) mass spectrometry in a total of 286 consecutive samples retrieved from women who presented with signs or symptoms of preterm labor or preterm premature rupture of the membranes. Inflammation and/or bleeding proteomic patterns were detected in 32% (92/286) of the SELDI tracings. In the remaining tracings, a hierarchical algorithm was applied based on descriptors quantifying similarity/dissimilarity among proteomic fingerprints. This allowed identification of a novel profile (Q-profile) based on the presence of 5 SELDI peaks in the 10-12.5 kDa mass area. Women displaying the Q-profile (mean+/-SD, gestational age: 25+/-4 weeks, n = 40) were more likely to deliver preterm despite expectant management in the context of intact membranes and normal amniotic fluid clinical results. Utilizing identification-centered proteomics techniques (fluorescence two-dimensional differential gel electrophoresis, robotic tryptic digestion and mass spectrometry) coupled with Protein ANalysis THrough Evolutionary Relationships (PANTHER) ontological classifications, we determined that in amniotic fluids with Q-profile the differentially expressed proteins are primarily involved in non-inflammatory biological processes such as protein metabolism, signal transduction and transport.

Conclusion/significance: Proteomic profiling of amniotic fluid coupled with non-hierarchical bioinformatics algorithms identified a subgroup of patients at risk for preterm birth in the absence of intra-amniotic inflammation or bleeding, suggesting a novel pathogenetic pathway leading to preterm birth. The altered proteins may offer opportunities for therapeutical intervention and future drug development to prevent prematurity.

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Biomarker peaks in the 10–12.5 kDa hypervariable region (Q-profile).A: Five SELDI peaks (Q1–Q5 denoted by green arrows) in the 10–12.5 kDa mass region appeared in a subgroup of the SELDI tracings analyzed (Patients 1 and 2 are examples). The third tracing (Patient 3) shows the lack of biomarkers in a woman that delivered at term. R denotes a reference protein peak present in all fluid samples which corresponds to a fragment of beta-2 microglobulin. B: experimental masses (average and 95% confidence interval (95%CI) for the five biomarker components of the Q-profile.
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pone-0002049-g002: Biomarker peaks in the 10–12.5 kDa hypervariable region (Q-profile).A: Five SELDI peaks (Q1–Q5 denoted by green arrows) in the 10–12.5 kDa mass region appeared in a subgroup of the SELDI tracings analyzed (Patients 1 and 2 are examples). The third tracing (Patient 3) shows the lack of biomarkers in a woman that delivered at term. R denotes a reference protein peak present in all fluid samples which corresponds to a fragment of beta-2 microglobulin. B: experimental masses (average and 95% confidence interval (95%CI) for the five biomarker components of the Q-profile.

Mentions: A novel computational algorithm was employed to analyze the proteomic information between 500 to 300,000 Da in our experimental conditions. From a bioinformatics perspective, SELDI tracings display silent areas alternating with hypervariable areas. Silent areas are mass ranges devoid of proteomic information and are identified by their similarity with the tracings obtained with the PBS diluent alone. In contrast, hypervariable areas are the mass ranges rich in potential biomarker peaks and are delineated by the high level of dissimilarity from the PBS tracings. For the purpose of reducing complexity, our algorithm first eliminated silent areas while extracting hypervariable areas. We next performed a hierarchical clustering of the tracings based on their similarity/dissimilarity in peaks present in hypervariable areas. Presence or absence of peaks was converted to binary strings with equal number of attributes and a hierarchical clustering algorithm applied. From the several hypervariable areas analyzed, we focused our attention on the mass area between 10 to 12.5 kDa due to the non-random clustering of the tracings based on a complex of five peaks in this region which we named the Q-profile (Figure 2A). The peak components are labeled Q1–Q5.


Multidimensional proteomics analysis of amniotic fluid to provide insight into the mechanisms of idiopathic preterm birth.

Buhimschi IA, Zhao G, Rosenberg VA, Abdel-Razeq S, Thung S, Buhimschi CS - PLoS ONE (2008)

Biomarker peaks in the 10–12.5 kDa hypervariable region (Q-profile).A: Five SELDI peaks (Q1–Q5 denoted by green arrows) in the 10–12.5 kDa mass region appeared in a subgroup of the SELDI tracings analyzed (Patients 1 and 2 are examples). The third tracing (Patient 3) shows the lack of biomarkers in a woman that delivered at term. R denotes a reference protein peak present in all fluid samples which corresponds to a fragment of beta-2 microglobulin. B: experimental masses (average and 95% confidence interval (95%CI) for the five biomarker components of the Q-profile.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2315798&req=5

pone-0002049-g002: Biomarker peaks in the 10–12.5 kDa hypervariable region (Q-profile).A: Five SELDI peaks (Q1–Q5 denoted by green arrows) in the 10–12.5 kDa mass region appeared in a subgroup of the SELDI tracings analyzed (Patients 1 and 2 are examples). The third tracing (Patient 3) shows the lack of biomarkers in a woman that delivered at term. R denotes a reference protein peak present in all fluid samples which corresponds to a fragment of beta-2 microglobulin. B: experimental masses (average and 95% confidence interval (95%CI) for the five biomarker components of the Q-profile.
Mentions: A novel computational algorithm was employed to analyze the proteomic information between 500 to 300,000 Da in our experimental conditions. From a bioinformatics perspective, SELDI tracings display silent areas alternating with hypervariable areas. Silent areas are mass ranges devoid of proteomic information and are identified by their similarity with the tracings obtained with the PBS diluent alone. In contrast, hypervariable areas are the mass ranges rich in potential biomarker peaks and are delineated by the high level of dissimilarity from the PBS tracings. For the purpose of reducing complexity, our algorithm first eliminated silent areas while extracting hypervariable areas. We next performed a hierarchical clustering of the tracings based on their similarity/dissimilarity in peaks present in hypervariable areas. Presence or absence of peaks was converted to binary strings with equal number of attributes and a hierarchical clustering algorithm applied. From the several hypervariable areas analyzed, we focused our attention on the mass area between 10 to 12.5 kDa due to the non-random clustering of the tracings based on a complex of five peaks in this region which we named the Q-profile (Figure 2A). The peak components are labeled Q1–Q5.

Bottom Line: Women displaying the Q-profile (mean+/-SD, gestational age: 25+/-4 weeks, n = 40) were more likely to deliver preterm despite expectant management in the context of intact membranes and normal amniotic fluid clinical results.Utilizing identification-centered proteomics techniques (fluorescence two-dimensional differential gel electrophoresis, robotic tryptic digestion and mass spectrometry) coupled with Protein ANalysis THrough Evolutionary Relationships (PANTHER) ontological classifications, we determined that in amniotic fluids with Q-profile the differentially expressed proteins are primarily involved in non-inflammatory biological processes such as protein metabolism, signal transduction and transport.The altered proteins may offer opportunities for therapeutical intervention and future drug development to prevent prematurity.

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven, Connecticut, United States of America. irina.buhimschi@yale.edu

ABSTRACT

Background: Though recent advancement in proteomics has provided a novel perspective on several distinct pathogenetic mechanisms leading to preterm birth (inflammation, bleeding), the etiology of most preterm births still remains elusive. We conducted a multidimensional proteomic analysis of the amniotic fluid to identify pathways related to preterm birth in the absence of inflammation or bleeding.

Methodology/principal findings: A proteomic fingerprint was generated from fresh amniotic fluid using surface-enhanced laser desorbtion ionization time of flight (SELDI-TOF) mass spectrometry in a total of 286 consecutive samples retrieved from women who presented with signs or symptoms of preterm labor or preterm premature rupture of the membranes. Inflammation and/or bleeding proteomic patterns were detected in 32% (92/286) of the SELDI tracings. In the remaining tracings, a hierarchical algorithm was applied based on descriptors quantifying similarity/dissimilarity among proteomic fingerprints. This allowed identification of a novel profile (Q-profile) based on the presence of 5 SELDI peaks in the 10-12.5 kDa mass area. Women displaying the Q-profile (mean+/-SD, gestational age: 25+/-4 weeks, n = 40) were more likely to deliver preterm despite expectant management in the context of intact membranes and normal amniotic fluid clinical results. Utilizing identification-centered proteomics techniques (fluorescence two-dimensional differential gel electrophoresis, robotic tryptic digestion and mass spectrometry) coupled with Protein ANalysis THrough Evolutionary Relationships (PANTHER) ontological classifications, we determined that in amniotic fluids with Q-profile the differentially expressed proteins are primarily involved in non-inflammatory biological processes such as protein metabolism, signal transduction and transport.

Conclusion/significance: Proteomic profiling of amniotic fluid coupled with non-hierarchical bioinformatics algorithms identified a subgroup of patients at risk for preterm birth in the absence of intra-amniotic inflammation or bleeding, suggesting a novel pathogenetic pathway leading to preterm birth. The altered proteins may offer opportunities for therapeutical intervention and future drug development to prevent prematurity.

Show MeSH
Related in: MedlinePlus