Michael T. Baer

Bio: Michael T. Baer is an academic researcher from Cold Spring Harbor Laboratory. The author has contributed to research in topics: Macrophage & Porphyromonas gingivalis. The author has an hindex of 5, co-authored 5 publications receiving 6707 citations. Previous affiliations of Michael T. Baer include Boston Medical Center & Boston University.

Landscape of transcription in human cells

Abstract: Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.

The K1 Serotype Capsular Polysaccharide of Porphyromonas gingivalis Elicits Chemokine Production from Murine Macrophages That Facilitates Cell Migration

Abstract: Porphyromonas gingivalis is the principal organism associated with aggressive forms of generalized periodontal disease. Previous reports have suggested that encapsulated P. gingivalis strains are more virulent than unencapsulated strains; however, the contribution of capsular polysaccharide (CPS) to the virulence of this organism is poorly understood. Since periodontal disease presents with a complex inflammatory cell lesion comprised of neutrophils and monocytes, we cultured murine peritoneal macrophages with heat-killed P. gingivalis W83, CPS purified from P. gingivalis strain W83, and the seven known serotype-specific P. gingivalis CPS and assessed the ability of supernatant fluids produced by challenged macrophages to attract naive inflammatory cells. We also defined JE/MCP-1, KC, MIP-2, and RANTES production in response to the P. gingivalis CPS antigens. We observed that supernatant fluids collected from macrophages incubated with P. gingivalis W83 and serotype K1 CPS stimulated the migration of naive murine bone marrow-derived polymorphonuclear leukocytes in an in vitro cell migration chamber. CPS from W83 and the K1 serotype elicited potent chemokine secretion patterns for macrophages, while those specific to serotypes K2 to K7 were significantly less stimulatory. Reverse transcription-PCR and enzyme-linked immunosorbent assay revealed JE/MCP-1, KC, MIP-2, and RANTES expression from murine macrophages which had been challenged with purified P. gingivalis W83 CPS. Chemokine production appeared to be dependent on both the dose of and time of exposure to P. gingivalis W83 CPS. These data demonstrate that the P. gingivalis serotype K1 CPS elicits chemokine production from phagocytic cells. Furthermore, these data suggest that the host response to this antigen may contribute to the formation of the inflammatory cell lesion observed during P. gingivalis-elicited periodontal disease.

Scavenger receptor A is expressed by macrophages in response to Porphyromonas gingivalis, and participates in TNF-alpha expression.

Abstract: Introduction: Porphyromonas gingivalis is a periodontopathic bacterium closely associated with generalized aggressive periodontal disease. Pattern recognition receptors (PRRs) participate in host response to this organism. It is likely that PRRs not previously recognized as part of the host response to P. gingivalis also participate in host response to this organism. Methods and Results: Employing qRT-PCR, we observed increased msr1 gene expression at 2, 6, and 24 h of culture with P. gingivalis strain 381. Flow cytometry revealed increased surface expression of SR-A protein by the 24 h time point. Macrophages cultured with an attachment impaired P. gingivalis fimA- mutant (DPG3) expressed intermediate levels of SR-A expression. Heat-killed P. gingivalis stimulated SR-A expression similar to live bacteria, and purified P. gingivalis capsular polysaccharide stimulated macrophage SR-A expression, indicating that live whole organisms are not necessary for SR-A protein expression in macrophage response. As SR-A is known to play a role in lipid uptake by macrophages, we tested the ability of low-density lipoprotein (LDL) to influence the SR-A response of macrophages to P. gingivalis, and observed no effect of LDL on P. gingivalis-elicited SR-A expression. Lastly, we observed that SR-A knockout (SR-A−/−) mouse macrophages produced significantly more tumor necrosis factor (TNF)-α than wild type mouse macrophages cultured with P. gingivalis. Conclusion: These data identify that SR-A is expressed by macrophages in response to P. gingivalis, and support that this molecule plays a role in TNF-α production by macrophages to this organism.

Role of MyD88-dependent and MyD88-independent signaling in Porphyromonas gingivalis-elicited macrophage foam cell formation.

Abstract: Clinical studies and experimental modeling identify a potential link between periodontal disease and periodontal pathogens such as Porphyromonas gingivalis and atherosclerosis and formation of macrophage foam cells. Toll-like receptors and molecules governing their intracellular signaling pathways such as MyD88 play roles in atherosclerosis, as well as host response to P. gingivalis. The aim of this study was to define roles of MyD88 and TRIF during macrophage foam cell formation in response to P. gingivalis. In the presence of human low-density lipoprotein (LDL) mouse bone-marrow-derived macrophages (BMφ) cultured with P. gingivalis responded with significant reduction in tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). The BMφ stained strongly with oil red O, regardless of whether bacterial challenge occurred concurrent with or before LDL treatment. Heat-killed P. gingivalis stimulated foam cell formation in a similar way to live bacteria. The BMφ from MyD88-knockout and Lps2 mice revealed a significant role for MyD88, and a minor role for TRIF in P. gingivalis-elicited foam cell formation. Porphyromonas gingivalis-elicited TNF-α and IL-6 were affected by MyD88 ablation and to a lesser extent by TRIF status. These data indicate that LDL affects the TNF-α and IL-6 response of macrophages to P. gingivalis challenge and that MyD88 and TRIF play important roles in P. gingivalis-elicited foam cell formation.

STAR: ultrafast universal RNA-seq aligner

Abstract: Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

An integrated encyclopedia of DNA elements in the human genome

Abstract: The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

Tissue-based map of the human proteome

Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

An integrated encyclopedia of DNA elements in the human genome.

Abstract: The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

NCBI GEO: archive for functional genomics data sets—update

Abstract: The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.