1
|
Zhang B, Zhang F, Lu F, Wang J, Zhou W, Wang H, Yu B. Reduced cell invasion may be a characteristic of placental defects in pregnant women of advanced maternal age at single-cell level. J Zhejiang Univ Sci B 2022; 23:747-759. [PMID: 36111571 DOI: 10.1631/jzus.b2101024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The mechanisms underlying pregnancy complications caused by advanced maternal age (AMA) remain unclear. We analyzed the cellular signature and transcriptomes of human placentas in AMA women to elucidate these mechanisms. Placental tissues from two AMA women and two controls were used for single-cell RNA-sequencing (scRNA-seq). Controls consisted of AMA women who did not experience any pregnancy complications and pregnant women below the age of 35 years without pregnancy complications. Trophoblast cells were obtained from the placentas of another six pregnant women (three AMA women and three controls), and in-vitro transwell assays were conducted to observe the cell invasion ability. Thirty additional samples (from 15 AMA women and 15 controls) were analyzed to verify the specific expression of serine protease inhibitor clade E member 1 (SERPINE1). Preliminary study of the role of SERPINE1 in cell invasion was carried out with HTR8-S/Vneo cells. High-quality transcriptomes of 27 607 cells were detected. Three types of trophoblast cells were detected, which were further classified into eight subtypes according to differences in gene expression and Gene Ontology (GO) function. We identified 110 differentially expressed genes (DEGs) in trophoblast cells between the AMA and control groups, and the DEGs were enriched in multiple pathways related to cell invasion. In-vitro transwell assays suggested that the invading trophoblast cells in AMA women were reduced. SERPINE1 was specifically expressed in the trophoblast, and its expression was higher in AMA women (P<0.05). Transfection of human SERPINE1 (hSERPINE1) into HTR8-S/Vneo trophoblast cells showed fewer invading cells in the hSERPINE1 group. Impaired cell invasion may underlie the increased risk of adverse pregnancy outcomes in AMA women. Abnormal expression of SERPINE1 in extravillous trophoblast (EVT) cells appears to play an important role.
Collapse
Affiliation(s)
- Bin Zhang
- Department of Medical Genetics, Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou 213000, China
| | - Feng Zhang
- Department of Medical Genetics, Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou 213000, China
| | - Fengying Lu
- Department of Medical Genetics, Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou 213000, China
| | - Jing Wang
- Department of Medical Genetics, Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou 213000, China
| | - Wenbai Zhou
- Department of Medical Genetics, Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou 213000, China
| | - Huihui Wang
- Department of Medical Genetics, Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou 213000, China
| | - Bin Yu
- Department of Medical Genetics, Changzhou Maternal and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou 213000, China.
| |
Collapse
|
2
|
Ghaemi MS, DiGiulio DB, Contrepois K, Callahan B, Ngo TTM, Lee-McMullen B, Lehallier B, Robaczewska A, Mcilwain D, Rosenberg-Hasson Y, Wong RJ, Quaintance C, Culos A, Stanley N, Tanada A, Tsai A, Gaudilliere D, Ganio E, Han X, Ando K, McNeil L, Tingle M, Wise P, Maric I, Sirota M, Wyss-Coray T, Winn VD, Druzin ML, Gibbs R, Darmstadt GL, Lewis DB, Partovi Nia V, Agard B, Tibshirani R, Nolan G, Snyder MP, Relman DA, Quake SR, Shaw GM, Stevenson DK, Angst MS, Gaudilliere B, Aghaeepour N. Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. Bioinformatics 2019; 35:95-103. [PMID: 30561547 PMCID: PMC6298056 DOI: 10.1093/bioinformatics/bty537] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 06/22/2018] [Accepted: 07/02/2018] [Indexed: 12/12/2022] Open
Abstract
Motivation Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Mohammad Sajjad Ghaemi
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, QC, Canada
- Groupe d’Études et de Recherche en Analyse des Décision (GERAD), Montréal, QC, Canada
- Centre Interuniversitaire de Recherche sur les Réseaux d’Entreprise, la Logistique et le Transport (CIRRELT), Montréal, QC, Canada
| | - Daniel B DiGiulio
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Benjamin Callahan
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA
| | - Thuy T M Ngo
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute and Department of Molecular and Medical Genetics, Oregon Health Sciences University, Portland, OR, USA
| | | | - Benoit Lehallier
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Anna Robaczewska
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - David Mcilwain
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Yael Rosenberg-Hasson
- Institute for Immunity, Transplantation and Infection, Human Immune Monitoring Center Stanford, CA, USA
| | - Ronald J Wong
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Cecele Quaintance
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Natalie Stanley
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Athena Tanada
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Amy Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Dyani Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Edward Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiaoyuan Han
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Kazuo Ando
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Leslie McNeil
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Martha Tingle
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Paul Wise
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Ivana Maric
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Marina Sirota
- Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA
- Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Virginia D Winn
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Maurice L Druzin
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Ronald Gibbs
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Gary L Darmstadt
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - David B Lewis
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Vahid Partovi Nia
- Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, QC, Canada
- Groupe d’Études et de Recherche en Analyse des Décision (GERAD), Montréal, QC, Canada
| | - Bruno Agard
- Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, QC, Canada
- Centre Interuniversitaire de Recherche sur les Réseaux d’Entreprise, la Logistique et le Transport (CIRRELT), Montréal, QC, Canada
| | - Robert Tibshirani
- Departments of Biomedical Data Sciences and Statistics, Stanford University, Stanford, CA, USA
- Department of Statistics, Stanford University School of Medicine, Stanford, CA, USA
| | - Garry Nolan
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - David A Relman
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Stephen R Quake
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Gary M Shaw
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - David K Stevenson
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| |
Collapse
|
3
|
Aghaeepour N, Lehallier B, Baca Q, Ganio EA, Wong RJ, Ghaemi MS, Culos A, El-Sayed YY, Blumenfeld YJ, Druzin ML, Winn VD, Gibbs RS, Tibshirani R, Shaw GM, Stevenson DK, Gaudilliere B, Angst MS. A proteomic clock of human pregnancy. Am J Obstet Gynecol 2018; 218:347.e1-347.e14. [PMID: 29277631 DOI: 10.1016/j.ajog.2017.12.208] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2017] [Revised: 11/24/2017] [Accepted: 12/18/2017] [Indexed: 12/20/2022]
Abstract
BACKGROUND Early detection of maladaptive processes underlying pregnancy-related pathologies is desirable because it will enable targeted interventions ahead of clinical manifestations. The quantitative analysis of plasma proteins features prominently among molecular approaches used to detect deviations from normal pregnancy. However, derivation of proteomic signatures sufficiently predictive of pregnancy-related outcomes has been challenging. An important obstacle hindering such efforts were limitations in assay technology, which prevented the broad examination of the plasma proteome. OBJECTIVE The recent availability of a highly multiplexed platform affording the simultaneous measurement of 1310 plasma proteins opens the door for a more explorative approach. The major aim of this study was to examine whether analysis of plasma collected during gestation of term pregnancy would allow identifying a set of proteins that tightly track gestational age. Establishing precisely timed plasma proteomic changes during term pregnancy is a critical step in identifying deviations from regular patterns caused by fetal and maternal maladaptations. A second aim was to gain insight into functional attributes of identified proteins and link such attributes to relevant immunological changes. STUDY DESIGN Pregnant women participated in this longitudinal study. In 2 subsequent sets of 21 (training cohort) and 10 (validation cohort) women, specific blood specimens were collected during the first (7-14 weeks), second (15-20 weeks), and third (24-32 weeks) trimesters and 6 weeks postpartum for analysis with a highly multiplexed aptamer-based platform. An elastic net algorithm was applied to infer a proteomic model predicting gestational age. A bootstrapping procedure and piecewise regression analysis was used to extract the minimum number of proteins required for predicting gestational age without compromising predictive power. Gene ontology analysis was applied to infer enrichment of molecular functions among proteins included in the proteomic model. Changes in abundance of proteins with such functions were linked to immune features predictive of gestational age at the time of sampling in pregnancies delivering at term. RESULTS An independently validated model consisting of 74 proteins strongly predicted gestational age (P = 3.8 × 10-14, R = 0.97). The model could be reduced to 8 proteins without losing its predictive power (P = 1.7 × 10-3, R = 0.91). The 3 top ranked proteins were glypican 3, chorionic somatomammotropin hormone, and granulins. Proteins activating the Janus kinase and signal transducer and activator of transcription pathway were enriched in the proteomic model, chorionic somatomammotropin hormone being the top-ranked protein. Abundance of chorionic somatomammotropin hormone strongly correlated with signal transducer and activator of transcription-5 signaling activity in CD4 T cells, the endogenous cell-signaling event most predictive of gestational age. CONCLUSION Results indicate that precisely timed changes in the plasma proteome during term pregnancy mirror a proteomic clock. Importantly, the combined use of several plasma proteins was required for accurate prediction. The exciting promise of such a clock is that deviations from its regular chronological profile may assist in the early diagnoses of pregnancy-related pathologies, and point to underlying pathophysiology. Functional analysis of the proteomic model generated the novel hypothesis that chrionic somatomammotropin hormone may critically regulate T-cell function during pregnancy.
Collapse
Affiliation(s)
- Nima Aghaeepour
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA
| | - Benoit Lehallier
- Department of Neurology and Neurological Science, Stanford University School of Medicine, Stanford, CA
| | - Quentin Baca
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA
| | - Ed A Ganio
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA
| | - Ronald J Wong
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Mohammad S Ghaemi
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA
| | - Yasser Y El-Sayed
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Yair J Blumenfeld
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Maurice L Druzin
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Virginia D Winn
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Ronald S Gibbs
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA
| | - Rob Tibshirani
- Department of Biomedical Data Sciences and Statistics, Stanford University School of Medicine, Stanford, CA
| | - Gary M Shaw
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - David K Stevenson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA.
| |
Collapse
|
4
|
Sundaram KM, Zhang Y, Mitra AK, Kouadio JLK, Gwin K, Kossiakoff AA, Roman BB, Lengyel E, Piccirilli JA. Prolactin Receptor-Mediated Internalization of Imaging Agents Detects Epithelial Ovarian Cancer with Enhanced Sensitivity and Specificity. Cancer Res 2017; 77:1684-1696. [PMID: 28202518 DOI: 10.1158/0008-5472.can-16-1454] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 12/02/2016] [Accepted: 12/21/2016] [Indexed: 01/24/2023]
Abstract
Poor prognosis of ovarian cancer, the deadliest of the gynecologic malignancies, reflects major limitations associated with detection and diagnosis. Current methods lack high sensitivity to detect small tumors and high specificity to distinguish malignant from benign tissue, both impeding diagnosis of early and metastatic cancer stages and leading to costly and invasive surgeries. Tissue microarray analysis revealed that >98% of ovarian cancers express the prolactin receptor (PRLR), forming the basis of a new molecular imaging strategy. We fused human placental lactogen (hPL), a specific and tight binding PRLR ligand, to magnetic resonance imaging (gadolinium) and near-infrared fluorescence imaging agents. Both in tissue culture and in mouse models, these imaging bioconjugates underwent selective internalization into ovarian cancer cells via PRLR-mediated endocytosis. Compared with current clinical MRI techniques, this targeted approach yielded both enhanced signal-to-noise ratio from accumulation of signal via selective internalization and improved specificity conferred by PRLR upregulation in malignant ovarian cancer. These features endow PRLR-targeted imaging with the potential to transform ovarian cancer detection. Cancer Res; 77(7); 1684-96. ©2017 AACR.
Collapse
Affiliation(s)
- Karthik M Sundaram
- Department of Biochemistry & Molecular Biology, and Chemistry, The University of Chicago, Chicago, Illinois
| | - Yilin Zhang
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology, The University of Chicago, Chicago, Illinois
| | - Anirban K Mitra
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology, The University of Chicago, Chicago, Illinois
| | - Jean-Louis K Kouadio
- Department of Biochemistry & Molecular Biology, and Chemistry, The University of Chicago, Chicago, Illinois
| | - Katja Gwin
- Department of Pathology, The University of Chicago, Chicago, Illinois
| | - Anthony A Kossiakoff
- Department of Biochemistry & Molecular Biology, and Chemistry, The University of Chicago, Chicago, Illinois
| | - Brian B Roman
- Department of Radiology, The University of Chicago, Chicago, Illinois
| | - Ernst Lengyel
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology, The University of Chicago, Chicago, Illinois.
| | - Joseph A Piccirilli
- Department of Biochemistry & Molecular Biology, and Chemistry, The University of Chicago, Chicago, Illinois.
| |
Collapse
|
5
|
Dourado DFAR, Flores SC. Modeling and fitting protein-protein complexes to predict change of binding energy. Sci Rep 2016; 6:25406. [PMID: 27173910 PMCID: PMC4865953 DOI: 10.1038/srep25406] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Accepted: 04/18/2016] [Indexed: 01/18/2023] Open
Abstract
It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.
Collapse
Affiliation(s)
- Daniel F A R Dourado
- Department of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Biomedical Center Box 596, 751 24, Uppsala, Sweden
| | - Samuel Coulbourn Flores
- Department of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Biomedical Center Box 596, 751 24, Uppsala, Sweden
| |
Collapse
|
6
|
Rizk SS, Kouadio JLK, Szymborska A, Duguid EM, Mukherjee S, Zheng J, Clevenger CV, Kossiakoff AA. Engineering synthetic antibody binders for allosteric inhibition of prolactin receptor signaling. Cell Commun Signal 2015; 13:1. [PMID: 25589173 PMCID: PMC4300558 DOI: 10.1186/s12964-014-0080-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Accepted: 12/17/2014] [Indexed: 11/18/2022] Open
Abstract
Background Many receptors function by binding to multiple ligands, each eliciting a distinct biological output. The extracellular domain of the human prolactin receptor (hPRL-R) uses an identical epitope to bind to both prolactin (hPRL) and growth hormone (hGH), yet little is known about how each hormone binding event triggers the appropriate response. Findings Here, we utilized a phage display library to generate synthetic antibodies (sABs) that preferentially modulate hPRL-R function in a hormone-dependent fashion. We determined the crystal structure of a sAB-hPRL-R complex, which revealed a novel allosteric mechanism of antagonism, whereby the sAB traps the receptor in a conformation more suitable for hGH binding than hPRL. This was validated by examining the effect of the sABs on hormone internalization via the hPRL-R and its downstream signaling pathway. Conclusions The findings suggest that subtle structural changes in the extracellular domain of hPRL-R induced by each hormone determine the biological output triggered by hormone binding. We conclude that sABs generated by phage display selection can detect these subtle structural differences, and therefore can be used to dissect the structural basis of receptor-ligand specificity. Electronic supplementary material The online version of this article (doi:10.1186/s12964-014-0080-8) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Shahir S Rizk
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA. .,Current Address: Boler -Parseghian Center for Rare and Neglected Diseases, University of Notre Dame, Notre Dame, IN, USA.
| | - Jean-Louis K Kouadio
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA. .,Current Address: Monsanto Co. 700 Chesterfield Parkway, Chesterfield, MO, USA.
| | - Anna Szymborska
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA. .,Current Address: Max Delbrueck Center for Molecular Medicine, Berlin, Germany.
| | - Erica M Duguid
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA.
| | - Somnath Mukherjee
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA.
| | - Jiamao Zheng
- Department of Pathology, Northwestern University, Chicago, IL, USA.
| | - Charles V Clevenger
- Department of Pathology, Northwestern University, Chicago, IL, USA. .,Current Address: Department of Pathology, Virginia Commonwealth University, Richmond, VA, USA.
| | - Anthony A Kossiakoff
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA.
| |
Collapse
|
7
|
Paterson RW, Toombs J, Slattery CF, Schott JM, Zetterberg H. Biomarker modelling of early molecular changes in Alzheimer's disease. Mol Diagn Ther 2014; 18:213-27. [PMID: 24281842 DOI: 10.1007/s40291-013-0069-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The preclinical phase of Alzheimer's disease (AD) occurs years, possibly decades, before the onset of clinical symptoms. Being able to detect the very earliest stages of AD is critical to improving understanding of AD biology, and identifying individuals at greatest risk of developing clinical symptoms with a view to treating AD pathophysiology before irreversible neurodegeneration occurs. Studies of dominantly inherited AD families and longitudinal studies of sporadic AD have contributed to knowledge of the earliest AD biomarkers. Here we appraise this evidence before reviewing novel, particularly fluid, biomarkers that may provide insights into AD pathogenesis and relate these to existing hypothetical disease models.
Collapse
Affiliation(s)
- Ross W Paterson
- Dementia Research Centre, Department of Neurodegeneration, UCL Institute of Neurology, London, UK,
| | | | | | | | | |
Collapse
|
8
|
Tuttle TR, Hugo ER, Tong WS, Ben-Jonathan N. Placental lactogen is expressed but is not translated into protein in breast cancer. PLoS One 2014; 9:e87325. [PMID: 24475273 PMCID: PMC3901772 DOI: 10.1371/journal.pone.0087325] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2013] [Accepted: 12/20/2013] [Indexed: 11/24/2022] Open
Abstract
Introduction Several studies reported that the pregnancy-specific hormone placental lactogen (hPL) is expressed at both mRNA and protein levels in breast cancer. The overall objective was to establish hPL, the product of the CSH1 and CSH2 genes, as a biomarker for breast cancer. Methods CSH expression was determined at the mRNA level in breast cancer cell lines (BCC) and primary carcinomas by real-time and conventional PCR and the products verified as CSH1 by sequencing. Expression of hPL protein was examined by western blots and immuno-histochemistry, using commercial and custom-made polyclonal and monoclonal antibodies. Results Variable levels of CSH mRNA were detected in several BCC, and in some primary tumors. We detected a protein, slightly larger than recombinant hPL by western blotting using several antibodies, leading us to postulate that it represents an hPL variant (‘hPL’). Furthermore, some monoclonal antibodies detected ‘hPL’ by immunohistochemistry in breast carcinomas but not in normal breast. However, further examination revealed that these antibodies were non-specific, as efficient suppression of CSH mRNA by shRNA did not abolish the ‘hPL’ band. Custom-made monoclonal antibodies against recombinant hPL detected hPL of the correct size in placental lysate and hPL-overexpressing BCC, but not in unmodified cells or primary carcinomas. hPL protein was detected only when mRNA was increased several thousand fold. Conclusions We call into question previous reports of hPL expression in breast cancer which relied on mRNA levels as surrogates for protein and/or used improperly validated antibodies to measure hPL protein levels. Our data suggests that an inhibitory mechanism(s) prevents translation of CSH mRNA in breast cancer when not highly expressed. The mechanism by which translation of CSH mRNA is inhibited is intriguing and should be further investigated.
Collapse
Affiliation(s)
- Traci R. Tuttle
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Eric R. Hugo
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Wilson S. Tong
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Nira Ben-Jonathan
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
- * E-mail:
| |
Collapse
|
9
|
Abstract
Prolactin and the prolactin receptors are members of a family of hormone/receptor pairs which include GH, erythropoietin, and other ligand/receptor pairs. The mechanisms of these ligand/receptor pairs have broad similarities, including general structures, ligand/receptor stoichiometries, and activation of several common signaling pathways. But significant variations in the structural and mechanistic details are present among these hormones and their type 1 receptors. The prolactin receptor is particularly interesting because it can be activated by three sequence-diverse human hormones: prolactin, GH, and placental lactogen. This system offers a unique opportunity to compare the detailed molecular mechanisms of these related hormone/receptor pairs. This review critically evaluates selected literature that informs these mechanisms, compares the mechanisms of the three lactogenic hormones, compares the mechanism with those of other class 1 ligand/receptor pairs, and identifies information that will be required to resolve mechanistic ambiguities. The literature describes distinct mechanistic differences between the three lactogenic hormones and their interaction with the prolactin receptor and describes more significant differences between the mechanisms by which other related ligands interact with and activate their receptors.
Collapse
Affiliation(s)
- Charles L Brooks
- Departments of Veterinary Biosciences and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA.
| |
Collapse
|
10
|
Voorhees JL, Rao GV, Gordon TJ, Brooks CL. Zinc binding to human lactogenic hormones and the human prolactin receptor. FEBS Lett 2011; 585:1783-8. [PMID: 21510945 DOI: 10.1016/j.febslet.2011.04.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2010] [Revised: 02/28/2011] [Accepted: 04/08/2011] [Indexed: 11/29/2022]
Abstract
Zinc half sites are present in all human lactogenic hormones: human prolactin (hPRL), growth hormone (hGH), placental lactogens (hPL) and the hPRL receptor (hPRLr). The influence of divalent zinc (Zn(2+)) as measured by intrinsic fluorescence or FRET in each of these hormones is unique and is affected by the presence of varying stoichiometries of hPRLr. These data show that both Zn(2+) and hPRLr binding influence hPRL conformers in an interdependent fashion. Although each of these three lactogenic hormones bind hPRLr and induce a biological response that is sensitive to the presence of increasing concentrations of Zn(2+), each hormone is unique in the mechanistic details of this process.
Collapse
Affiliation(s)
- Jeffrey L Voorhees
- Ohio State Biochemistry Program, The Ohio State University, Columbus, OH 43210, United States.
| | | | | | | |
Collapse
|
11
|
Abstract
Human prolactin (hPRL) binds two human prolactin receptor molecules, creating active heterotrimeric complexes. Receptors bind dissimilar hormone surfaces termed site 1 and site 2 in an obligate ordered process. We sought to map the functional epitopes in site 1 of hPRL. Extensive alanine mutagenesis (102 of the 199 residues) showed approximately 40% of these mutant hPRLs changed the ΔG for site 1 receptor binding. Six of these residues are within 3.5 Å of the receptor and form the site 1 functional epitopes. We identified a set of noncovalent interactions between these six residues and the receptor. We identified a second group of site 1 residues that are between 3.5 and 5 Å from the receptor where alanine mutations reduced the affinity. This second group has noncovalent interactions with other hormone residues and stabilized the topology of the functional epitopes by linking these to the body of the protein. Finally, we identified a third group of residues that are outside site 1 (>5 Å) and extend to site 2 and whose mutation to alanine significantly weakened receptor binding at site 1 of prolactin. These three groups of residues form a contiguous structural motif between sites 1 and 2 of human prolactin and may constitute structural features that functionally couple sites 1 and 2. This work identifies the residues that form the functional epitopes for site 1 of human prolactin and also identifies a set of residues that support the concept that sites 1 and 2 are functionally coupled by an allosteric mechanism.
Collapse
Affiliation(s)
- Geeta Vittal Rao
- Ohio State Biophysics Program, Ohio State University, 1925 Coffey Road, Columbus, OH 43210, USA
| | | |
Collapse
|
12
|
Voorhees JL, Brooks CL. Obligate ordered binding of human lactogenic cytokines. J Biol Chem 2010; 285:20022-30. [PMID: 20427283 DOI: 10.1074/jbc.m109.084988] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Class 1 cytokines bind two receptors to create an active heterotrimeric complex. It has been argued that ligand binding to their receptors is an ordered process, but a structural mechanism describing this process has not been determined. We have previously described an obligate ordered binding mechanism for the human prolactin/prolactin receptor heterotrimeric complex. In this work we expand this conceptual understanding of ordered binding to include three human lactogenic hormones: prolactin, growth hormone, and placental lactogen. We independently blocked either of the two receptor binding sites of each hormone and used surface plasmon resonance to measure human prolactin receptor binding kinetics and stoichiometries to the remaining binding surface. When site 1 of any of the three hormones was blocked, site 2 could not bind the receptor. But blocking site 2 did not affect receptor binding at site 1, indicating a requirement for receptor binding to site 1 before site 2 binding. In addition we noted variable responses to the presence of zinc in hormone-receptor interaction. Finally, we performed Förster resonance energy transfer (FRET) analyses where receptor binding at subsaturating stoichiometries induced changes in FRET signaling, indicative of binding-induced changes in hormone conformation, whereas at receptor:hormone ratios in excess of 2:1 no additional changes in FRET signaling were observed. These results strongly support a conformationally mediated obligate-ordered receptor binding for each of the three lactogenic hormones.
Collapse
Affiliation(s)
- Jeffery L Voorhees
- The Ohio State Biochemistry Program, The Ohio State University, 1925 Coffey Rd., Columbus, OH 43210, USA
| | | |
Collapse
|
13
|
Clapp C, Thebault S, Jeziorski MC, Martínez De La Escalera G. Peptide hormone regulation of angiogenesis. Physiol Rev 2009; 89:1177-215. [PMID: 19789380 DOI: 10.1152/physrev.00024.2009] [Citation(s) in RCA: 121] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
It is now apparent that regulation of blood vessel growth contributes to the classical actions of hormones on development, growth, and reproduction. Endothelial cells are ideally positioned to respond to hormones, which act in concert with locally produced chemical mediators to regulate their growth, motility, function, and survival. Hormones affect angiogenesis either directly through actions on endothelial cells or indirectly by regulating proangiogenic factors like vascular endothelial growth factor. Importantly, the local microenvironment of endothelial cells can determine the outcome of hormone action on angiogenesis. Members of the growth hormone/prolactin/placental lactogen, the renin-angiotensin, and the kallikrein-kinin systems that exert stimulatory effects on angiogenesis can acquire antiangiogenic properties after undergoing proteolytic cleavage. In view of the opposing effects of hormonal fragments and precursor molecules, the regulation of the proteases responsible for specific protein cleavage represents an efficient mechanism for balancing angiogenesis. This review presents an overview of the actions on angiogenesis of the above-mentioned peptide hormonal families and addresses how specific proteolysis alters the final outcome of these actions in the context of health and disease.
Collapse
Affiliation(s)
- Carmen Clapp
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico.
| | | | | | | |
Collapse
|
14
|
Langenheim JF, Chen WY. Development of a novel ligand that activates JAK2/STAT5 signaling through a heterodimer of prolactin receptor and growth hormone receptor. J Recept Signal Transduct Res 2009; 29:107-12. [DOI: 10.1080/10799890902845252] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
|
15
|
Alvarez-Oxiley AV, de Sousa NM, Beckers JF. Native and recombinant bovine placental lactogens. Reprod Biol 2008; 8:85-106. [PMID: 18677398 DOI: 10.1016/s1642-431x(12)60006-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The bovine placenta produces a wide variety of proteins that are structurally and functionally similar to the pituitary proteins from the GH/PRL gene family. Bovine placental lactogen (bPL) is a 200-amino acid long glycoprotein hormone that exhibits both lactogenic and somatogenic properties. The apparent molecular masses of purified native (n) bPL molecules (31-33 kDa) exceed 23 041 Da, which is the theoretical molecular mass of the protein core. At least six isoelectric variants (pI: 4.85-6.3) of bPL were described in cotyledonary extracts and three different bPL isoforms (pI: 4.85-5.25) were found in fetal sera. The bPL molecules that are detected in higher concentrations in peripheral circulation exhibit a more acidic pI than those present in placental homogenates. This may reflect an important glycosylation process occurring just prior to the bPL secretion. The bPL mRNA is transcribed in trophectoderm binucleate cells starting from Day 30 of pregnancy until the end of gestation. In mothers, bPL is involved in the regulation of ovarian function, mammogenesis, lactogenesis, and pregnancy stage-dependent adaptation of nutrient supplies to the fetus. Due to the higher fetal, compared to maternal concentrations of circulating hormone, it has been suggested that bPL primarily targets fetal tissues.
Collapse
Affiliation(s)
- Andrea V Alvarez-Oxiley
- Laboratory of Animal Endocrinology and Reproduction, Faculty of Veterinary Medicine, University of Liege, Bd. de Colonster, 4000. Liege, Belgium
| | | | | |
Collapse
|
16
|
Jomain JB, Tallet E, Broutin I, Hoos S, van Agthoven J, Ducruix A, Kelly PA, Kragelund BB, England P, Goffin V. Structural and Thermodynamic Bases for the Design of Pure Prolactin Receptor Antagonists. J Biol Chem 2007; 282:33118-31. [PMID: 17785459 DOI: 10.1074/jbc.m704364200] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Competitive antagonists of the human prolactin (hPRL) receptor are a novel class of molecules of potential therapeutic interest in the context of cancer. We recently developed the pure antagonist Del1-9-G129R-hPRL by deleting the nine N-terminal residues of G129R-hPRL, a first generation partial antagonist. We determined the crystallographic structure of Del1-9-G129R-hPRL, which revealed no major change compared with wild type hPRL, indicating that its pure antagonistic properties are intrinsically due to the mutations. To decipher the molecular bases of pure antagonism, we compared the biological, physicochemical, and structural properties of numerous hPRL variants harboring N-terminal or Gly(129) mutations, alone or combined. The pure versus partial antagonistic properties of the multiple hPRL variants could not be correlated to differences in their affinities toward the hPRL receptor, especially at site 2 as determined by surface plasmon resonance. On the contrary, residual agonism of the hPRL variants was found to be inversely correlated to their thermodynamic stability, which was altered by all the Gly(129) mutations but not by those involving the N terminus. We therefore propose that residual agonism can be abolished either by further disrupting hormone site 2-receptor contacts by N-terminal deletion, as in Del1-9-G129R-hPRL, or by stabilizing hPRL and constraining its intrinsic flexibility, as in G129V-hPRL.
Collapse
Affiliation(s)
- Jean-Baptiste Jomain
- INSERM U845, Centre de Recherche Croissance et Signalisation, Equipe PRL, GH et Tumeurs, Faculté de Médecine Necker, 156 Rue de Vaugirard, Paris Cedex 15, France
| | | | | | | | | | | | | | | | | | | |
Collapse
|
17
|
Polgar N, Fogelgren B, Shipley JM, Csiszar K. Lysyl Oxidase Interacts with Hormone Placental Lactogen and Synergistically Promotes Breast Epithelial Cell Proliferation and Migration. J Biol Chem 2007; 282:3262-72. [PMID: 17130123 DOI: 10.1074/jbc.m609407200] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Lysyl oxidase (LOX), an extracellular amine oxidase, catalyzes the cross-linking of collagen and elastin. LOX has been also shown to play an essential role in promoting the invasive and metastatic potential of breast tumor cells. However, the LOX-interacting factors in these processes are not known. In this study, we identified placental lactogen (PL), a member of the growth hormone/prolactin hormone family, as a LOX-interacting partner using yeast two-hybrid screens. PL is normally only expressed in placental syncytiotrophoblasts, but PL genes are amplified and expressed in a high percentage of invasive ductal breast carcinomas. We confirmed LOX-PL interactions using far Western and solid phase binding assays. In activity assays, PL was not a substrate or inhibitor of LOX. We further demonstrated that PL is expressed in breast tumor epithelial cells and detected LOX-PL interactions by coimmunoprecipitation in invasive breast cancer cells. In MCF-10A normal breast epithelial cells stably expressing LOX, PL, or both, LOX had no effect on cell proliferation, PL alone increased proliferation by 49%, and coexpression of LOX and PL led to a 121% increase in cell proliferation. Unlike in tumor cells, LOX did not induce a more migratory phenotype in MCF-10A cells; nor did PL. However, their coexpression resulted in a 240% increase in cell migration, suggesting that these interactions may be highly relevant to the transition of epithelial cells toward a migratory phenotype during the development and progression of breast carcinoma and a significant role for LOX-PL interactions in epithelial cell behavior.
Collapse
Affiliation(s)
- Noemi Polgar
- Cardiovascular Research Center, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii 96822, USA
| | | | | | | |
Collapse
|
18
|
Reichmann D, Rahat O, Cohen M, Neuvirth H, Schreiber G. The molecular architecture of protein-protein binding sites. Curr Opin Struct Biol 2007; 17:67-76. [PMID: 17239579 DOI: 10.1016/j.sbi.2007.01.004] [Citation(s) in RCA: 147] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2006] [Revised: 12/13/2006] [Accepted: 01/10/2007] [Indexed: 11/16/2022]
Abstract
The formation of specific protein interactions plays a crucial role in most, if not all, biological processes, including signal transduction, cell regulation, the immune response and others. Recent advances in our understanding of the molecular architecture of protein-protein binding sites, which facilitates such diversity in binding affinity and specificity, are enabling us to address key questions. What is the amino acid composition of binding sites? What are interface hotspots? How are binding sites organized? What are the differences between tight and weak interacting complexes? How does water contribute to binding? Can the knowledge gained be translated into protein design? And does a universal code for binding exist, or is it the architecture and chemistry of the interface that enable diverse but specific binding solutions?
Collapse
Affiliation(s)
- Dana Reichmann
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel
| | | | | | | | | |
Collapse
|
19
|
Rich RL, Myszka DG. Survey of the year 2006 commercial optical biosensor literature. J Mol Recognit 2007; 20:300-66. [DOI: 10.1002/jmr.862] [Citation(s) in RCA: 97] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
|