Roberto Romero

Bio: Roberto Romero is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Amniotic fluid & Chorioamnionitis. The author has an hindex of 151, co-authored 1516 publications receiving 108321 citations. Previous affiliations of Roberto Romero include University of Michigan & Weizmann Institute of Science.

No Consistent Evidence for Microbiota in Murine Placental and Fetal Tissues

Abstract: The existence of a placental microbiota and in utero colonization of the fetus have been the subjects of recent debate. The objective of this study was to determine whether the placental and fetal tissues of mice harbor bacterial communities. Bacterial profiles of the placenta and fetal brain, lung, liver, and intestine samples were characterized through culture, quantitative real-time PCR (qPCR), and 16S rRNA gene sequencing. These profiles were compared to those of the maternal mouth, lung, liver, uterus, cervix, vagina, and intestine, as well as to background technical controls. Positive bacterial cultures from placental and fetal tissue samples were rare; of the 165 total bacterial cultures of placental tissue samples from the 11 mice included in this study, only nine yielded at least a single colony, and five of those nine positive cultures came from a single mouse. Cultures of fetal intestinal tissue samples yielded just a single bacterial isolate, Staphylococcus hominis, a common skin bacterium. Bacterial loads of placental and fetal brain, lung, liver, and intestinal tissues were not higher than those of DNA contamination controls and did not yield substantive 16S rRNA gene sequencing libraries. From all placental or fetal tissue samples (n = 51), there was only a single bacterial isolate that came from a fetal brain sample having a bacterial load higher than that of contamination controls and that was identified in sequence-based surveys of at least one of its corresponding maternal samples. Therefore, using multiple modes of microbiological inquiry, there was not consistent evidence of bacterial communities in the placental and fetal tissues of mice. IMPORTANCE The prevailing paradigm in obstetrics has been the sterile womb hypothesis, which posits that fetuses are first colonized by microorganisms during the delivery process. However, some are now suggesting that fetuses are consistently colonized in utero by microorganisms from microbial communities that inhabit the placenta and intra-amniotic environment. Given the established causal role of microbial invasion of the amniotic cavity (i.e., intra-amniotic infection) in pregnancy complications, especially preterm birth, if the in utero colonization hypothesis were true, there are several aspects of current understanding that will need to be reconsidered; these aspects include the magnitude of intra-amniotic microbial load required to cause disease and its potential influence on the ontogeny of the immune system. However, acceptance of the in utero colonization hypothesis is premature. Herein, we do not find consistent evidence for placental and fetal microbiota in mice using culture, qPCR, and DNA sequencing.

A role for CXCL13 (BCA-1) in pregnancy and intra-amniotic infection/inflammation

Abstract: Objectives. CXCL13 is a potent chemokine, produced by mature and recently recruited macrophages to sites of inflammation, which has antimicrobial and anti-angiogenic properties. The purpose of this study was to: (1) determine whether CXCL13 is present in maternal serum, umbilical cord blood, and amniotic fluid (AF); (2) to determine if AF concentration changes with intra-amniotic infection/inflammation (IAI); and (3) to localize the production of CXCL13 in chorioamniotic membranes and umbilical cord.Study design. A cross-sectional study on maternal serum was performed including patients in the following groups: (1) non-pregnant women (n = 20), (2) normal pregnant women (n = 49), (3) patients at term not in labor (n = 30), and (4) patients in spontaneous labor at term (n = 29). Umbilical cord blood was collected from term neonates with (n = 30) and without labor (n = 28). Amniotic fluid was obtained from patients in the following groups: (1) midtrimester (n = 65); (2) term not in labor (n = 22); (3) term i...

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.

Abstract: Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.