A microphysiological model of human trophoblast invasion during implantation.

Successful establishment of pregnancy requires adhesion of an embryo to the endometrium and subsequent invasion into the maternal tissue. Abnormalities in this critical process of implantation and placentation lead to many pregnancy complications. Here we present a microenigneered system to model a complex sequence of orchestrated multicellular events that plays an essential role in early pregnancy. Our implantation-on-a-chip is capable of reconstructing the three-dimensional structural organization of the maternal-fetal interface to model the invasion of specialized fetal extravillous trophoblasts into the maternal uterus. Using primary human cells isolated from clinical specimens, we demonstrate in vivo-like directional migration of extravillous trophoblasts towards a microengineered maternal vessel and their interactions with the endothelium necessary for vascular remodeling. Through parametric variation of the cellular microenvironment and proteomic analysis of microengineered tissues, we show the important role of decidualized stromal cells as a regulator of extravillous trophoblast migration. Furthermore, our study reveals previously unknown effects of pre-implantation maternal immune cells on extravillous trophoblast invasion. This work represents a significant advance in our ability to model early human pregnancy, and may enable the development of advanced in vitro platforms for basic and clinical research of human reproduction.

Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

Diurnal cycling of rhizosphere bacterial communities is associated with shifts in carbon metabolism.

BACKGROUND: The circadian clock regulates plant metabolic functions and is an important component in plant health and productivity. Rhizosphere bacteria play critical roles in plant growth, health, and development and are shaped primarily by soil communities. Using Illumina next-generation sequencing and high-resolution mass spectrometry, we characterized bacterial communities of wild-type (Col-0) Arabidopsis thaliana and an acyclic line (OX34) ectopically expressing the circadian clock-associated cca1 transcription factor, relative to a soil control, to determine how cycling dynamics affected the microbial community. Microbial communities associated with Brachypodium distachyon (BD21) were also evaluated. RESULTS: Significantly different bacterial community structures (P = 0.031) were observed in the rhizosphere of wild-type plants between light and dark cycle samples. Furthermore, 13% of the community showed cycling, with abundances of several families, including Burkholderiaceae, Rhodospirillaceae, Planctomycetaceae, and Gaiellaceae, exhibiting fluctuation in abundances relative to the light cycle. However, limited-to-no cycling was observed in the acyclic CCAox34 line or in soil controls. Significant cycling was also observed, to a lesser extent, in Brachypodium. Functional gene inference revealed that genes involved in carbohydrate metabolism were likely more abundant in near-dawn, dark samples. Additionally, the composition of organic matter in the rhizosphere showed a significant variation between dark and light cycles. CONCLUSIONS: The results of this study suggest that the rhizosphere bacterial community is regulated, to some extent, by the circadian clock and is likely influenced by, and exerts influences, on plant metabolism and productivity. The timing of bacterial cycling in relation to that of Arabidopsis further suggests that diurnal dynamics influence plant-microbe carbon metabolism and exchange. Equally important, our results suggest that previous studies done without relevance to time of day may need to be reevaluated with regard to the impact of diurnal cycles on the rhizosphere microbial community.

Identifying Aspects of the Post-Transcriptional Program Governing the Proteome of the Green Alga Micromonas pusilla.

Micromonas is a unicellular motile alga within the Prasinophyceae, a green algal group that is related to land plants. This picoeukaryote (<2 µm diameter) is widespread in the marine environment but is not well understood at the cellular level. Here, we examine shifts in mRNA and protein expression over the course of the day-night cycle using triplicated mid-exponential, nutrient replete cultures of Micromonas pusilla CCMP1545. Samples were collected at key transition points during the diel cycle for evaluation using high-throughput LC-MS proteomics. In conjunction, matched mRNA samples from the same time points were sequenced using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of M. pusilla. Similar to a prior study of the marine cyanobacterium Prochlorococcus, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as we observed in the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels from both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including codon usage as well as 3' UTR length and structure. Collectively, our studies provide insights into the regulation of the proteome over a diel cycle as well as the relationships between transcriptional and translational programs in the widespread marine green alga Micromonas.