Diabetes and obesity are two metabolic diseases characterized by insulin resistance and a low-grade inflammation. Seeking an inflammatory factor causative of the onset of insulin resistance, obesity, and diabetes, we have identified bacterial lipopolysaccharide (LPS) as a triggering factor. We found that normal endotoxemia increased or decreased during the fed or fasted state, respectively, on a nutritional basis and that a 4-week high-fat diet chronically increased plasma LPS concentration two to three times, a threshold that we have defined as metabolic endotoxemia. Importantly, a high-fat diet increased the proportion of an LPS-containing microbiota in the gut. When metabolic endotoxemia was induced for 4 weeks in mice through continuous subcutaneous infusion of LPS, fasted glycemia and insulinemia and whole-body, liver, and adipose tissue weight gain were increased to a similar extent as in high-fat-fed mice. In addition, adipose tissue F4/80-positive cells and markers of inflammation, and liver triglyceride content, were increased. Furthermore, liver, but not whole-body, insulin resistance was detected in LPS-infused mice. CD14 mutant mice resisted most of the LPS and high-fat diet-induced features of metabolic diseases. This new finding demonstrates that metabolic endotoxemia dysregulates the inflammatory tone and triggers body weight gain and diabetes. We conclude that the LPS/CD14 system sets the tone of insulin sensitivity and the onset of diabetes and obesity. Lowering plasma LPS concentration could be a potent strategy for the control of metabolic diseases.

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Metabolic endotoxemia initiates obesity and insulin resistance

This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.

Metagenomic biomarker discovery and explanation

The heme oxygenase (HO) system consists of two forms identified to date: the oxidative stress-inducible protein HO-1 (HSP32) and the constitutive isozyme HO-2. These proteins, which are different gene products, have little in common in primary structure, regulation, or tissue distribution. Both, however, catalyze oxidation of heme to biologically active molecules: iron, a gene regulator; biliverdin, an antioxidant; and carbon monoxide, a heme ligand. Finding the impressive heme-degrading activity of brain led to the suggestion that "HO in brain has functions aside from heme degradation" and to subsequent exploration of carbon monoxide as a promising and potentially significant messenger molecule. There is much parallelism between the biological actions and functions of the CO- and NO-generating systems; and their regulation is intimately linked. This review highlights the current information on molecular and biochemical properties of HO-1 and HO-2 and addresses the possible mechanisms for mutual regulatory interactions between the CO- and NO-generating systems.

THE HEME OXYGENASE SYSTEM:A Regulator of Second Messenger Gases

Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility. Bacteria have evolved various mechanisms to counter the problems imposed by their iron dependence, allowing them to achieve effective iron homeostasis under a range of iron regimes. Highly efficient iron acquisition systems are used to scavenge iron from the environment under iron-restricted conditions. In many cases, this involves the secretion and internalisation of extracellular ferric chelators called siderophores. Ferrous iron can also be directly imported by the G protein-like transporter, FeoB. For pathogens, host–iron complexes (transferrin, lactoferrin, haem, haemoglobin) are directly used as iron sources. Bacterial iron storage proteins (ferritin, bacterioferritin) provide intracellular iron reserves for use when external supplies are restricted, and iron detoxification proteins (Dps) are employed to protect the chromosome from iron-induced free radical damage. There is evidence that bacteria control their iron requirements in response to iron availability by down-regulating the expression of iron proteins during iron-restricted growth. And finally, the expression of the iron homeostatic machinery is subject to iron-dependent global control ensuring that iron acquisition, storage and consumption are geared to iron availability and that intracellular levels of free iron do not reach toxic levels.

Bacterial iron homeostasis

Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Integrative Genomics Viewer

Virulence factors of Porphyromonas gingivalis.

Recent advances in high-throughput RNA sequencing (RNA-seq) have enabled tremendous leaps forward in our understanding of bacterial transcriptomes. However, computational methods for analysis of bacterial transcriptome data have not kept pace with the large and growing data sets generated by RNA-seq technology. Here, we present new algorithms, specific to bacterial gene structures and transcriptomes, for analysis of RNA-seq data. The algorithms are implemented in an open source software system called Rockhopper that supports various stages of bacterial RNA-seq data analysis, including aligning sequencing reads to a genome, constructing transcriptome maps, quantifying transcript abundance, testing for differential gene expression, determining operon structures and visualizing results. We demonstrate the performance of Rockhopper using 2.1 billion sequenced reads from 75 RNA-seq experiments conducted with Escherichia coli, Neisseria gonorrhoeae, Salmonella enterica, Streptococcus pyogenes and Xenorhabdus nematophila. We find that the transcriptome maps generated by our algorithms are highly accurate when compared with focused experimental data from E. coli and N. gonorrhoeae, and we validate our system's ability to identify novel small RNAs, operons and transcription start sites. Our results suggest that Rockhopper can be used for efficient and accurate analysis of bacterial RNA-seq data, and that it can aid with elucidation of bacterial transcriptomes.

Computational analysis of bacterial RNA-Seq data

Invasion of host cells is believed to be an important strategy utilized by a number of pathogens, which affords them protection from the host immune system. The connective tissues of the periodontium are extremely well vascularized, which allows invading microorganisms, such as the periodontal pathogen Porphyromonas gingivalis, to readily enter the bloodstream. However, the ability of P. gingivalis to actively invade endothelial cells has not been previously examined. In this study, we demonstrate that P. gingivalis can invade bovine and human endothelial cells as assessed by an antibiotic protection assay and by transmission and scanning electron microscopy. P. gingivalis A7436 was demonstrated to adhere to and to invade fetal bovine heart endothelial cells (FBHEC), bovine aortic endothelial cells (BAEC), and human umbilical vein endothelial cells (HUVEC). Invasion efficiencies of 0.1, 0.2, and 0.3% were obtained with BAEC, HUVEC, and FBHEC, respectively. Invasion of FBHEC and BAEC by P. gingivalis A7436 assessed by electron microscopy revealed the formation of microvillus-like extensions around adherent bacteria followed by the engulfment of the pathogen within vacuoles. Invasion of BAEC by P. gingivalis A7436 was inhibited by cytochalasin D, nocodazole, staurosporine, protease inhibitors, and sodium azide, indicating that cytoskeletal rearrangements, protein phosphorylation, energy metabolism, and P. gingivalis proteases are essential for invasion. In contrast, addition of rifampin, nalidixic acid, and chloramphenicol had little effect on invasion, indicating that bacterial RNA, DNA, and de novo protein synthesis are not required for P. gingivalis invasion of endothelial cells. Likewise de novo protein synthesis by endothelial cells was not required for invasion by P. gingivalis. P. gingivalis 381 was demonstrated to adhere to and to invade BAEC (0.11 and 0.1% efficiency, respectively). However, adherence and invasion of the corresponding fimA mutant DPG3, which lacks the major fimbriae, was not detected. These results indicate that P. gingivalis can actively invade endothelial cells and that fimbriae are required for this process. P. gingivalis invasion of endothelial cells may represent another strategy utilized by this pathogen to thwart the host immune response.

https://iai.asm.org/content/iai/66/11/5337.full.pdf

Invasion of aortic and heart endothelial cells by Porphyromonas gingivalis.

Background— Infectious diseases have emerged as potential risk factors for cardiovascular disease (CVD). Epidemiological studies support a connection between periodontal disease, a chronic inflammatory disease of the supporting tissues of the teeth, and CVD. Methods and Results— To directly test the connection between periodontal disease and atherosclerosis, apoE−/− mice were orally challenged with the periodontal disease pathogen Porphyromonas gingivalis or an invasion-impaired P gingivalis fimbriae-deficient mutant (FimA−). Both wild-type P gingivalis and the FimA− mutant were detected in blood and aortic arch tissue of apoE−/− mice by PCR after challenge. ApoE−/− mice challenged with wild-type P gingivalis presented with increased atherosclerotic plaque and expressed the innate immune response markers Toll-like receptor (TLR)-2 and TLR-4 in aortic tissue. Despite detection of the FimA− mutant in the blood and in aortic arch tissue, apoE−/− mice challenged with the FimA− mutant did not present with peri...

Innate Immune Recognition of Invasive Bacteria Accelerates Atherosclerosis in Apolipoprotein E-Deficient Mice

Gram-negative pathogenic bacteria have evolved novel strategies to obtain iron from host haem-sequestering proteins. These include the production of specific outer membrane receptors that bind directly to host haem-sequestering proteins, secreted haem-binding proteins (haemophores) that bind haem/haemoglobin/haemopexin and deliver the complex to a bacterial cell surface receptor and bacterial proteases that degrade haem-sequestering proteins. Once removed from haem-sequestering proteins, haem may be transported via the bacterial outer membrane receptor into the cell. Recent studies have begun to define the steps by which haem is removed from bacterial haem proteins and transported into the cell. This review describes recent work on the discovery and characterization of these systems. Reference is also made to the transport of haem in serum (via haemoglobin, haemoglobin/haptoglobin, haemopexin, albumin and lipoproteins) and to mechanisms of iron removal from the haem itself (probably via a haem oxygenase pathway in which the protoporphyrin ring is degraded). Haem protein-receptor interactions are discussed in terms of the criteria that govern protein-protein interactions in general, and connections between haem transport and the emerging field of metal transport via metallochaperones are outlined.

https://onlinelibrary.wiley.com/doi/pdf/10.1046/j.1365-2958.2001.02231.x

Caroline A. Genco

Papers

Virulence factors of Porphyromonas gingivalis.

Computational analysis of bacterial RNA-Seq data

Invasion of aortic and heart endothelial cells by Porphyromonas gingivalis.

Innate Immune Recognition of Invasive Bacteria Accelerates Atherosclerosis in Apolipoprotein E-Deficient Mice

Emerging strategies in microbial haem capture.