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Mechanical loading, such as caused by exercise, stimulates bone formation by osteoblasts and increases bone strength, but the mechanisms are poorly understood. Osteocytes reside in bone matrix, sense changes in mechanical load, and produce signals that alter bone formation by osteoblasts. We report that the ion channel Piezo1 is required for changes in gene expression induced by fluid shear stress in cultured osteocytes and stimulation of Piezo1 by a small molecule agonist is sufficient to replicate the effects of fluid flow on osteocytes. Conditional deletion of Piezo1 in osteoblasts and osteocytes notably reduced bone mass and strength in mice. Conversely, administration of a Piezo1 agonist to adult mice increased bone mass, mimicking the effects of mechanical loading. These results demonstrate that Piezo1 is a mechanosensitive ion channel by which osteoblast lineage cells sense and respond to changes in mechanical load and identify a novel target for anabolic bone therapy. Bone size and strength depend on physical activity. Increased forces on the skeleton, such as those that occur during exercise, trigger more bone formation and make bones stronger. Conversely, reduced forces, caused for example by the lack physical activity, cause bone loss and increase the risk of fractures. Bones contain cells called osteocytes. These cells sense the forces exerted on bone and orchestrate bone formation in response. Calcium channels are one type of molecule that has been proposed to help osteocytes to sense forces. Calcium channels reside in the cell membrane and can change their structure to allow calcium ions to flow into the cell. Some of them allow calcium ions into the cell in direct response to physical forces, communicating to the cell that a force has been applied. These are called mechanosensitive ion channels. Until now, however, no specific calcium channels involved in force sensing had been identified in osteocytes. Li et al. searched for calcium channels in osteocytes, and found high levels of a mechanosensitive ion channel called Piezo1. Then, Li et al. made genetically modified mice that did not have any Piezo1 in these cells. The skeleton of these mice was small and weak. Moreover, the bones of these modified mice did not respond to forces like the bones of normal mice. To demonstrate this, Li et al. applied a short bout of increased force to the leg bones of unmodified mice and to those of the Piezo1 deficient mice. After two weeks, the bones of the unmodified mice had increased in thickness, whereas the bones lacking Piezo1 had not. A separate study by Sun, Chi et al. showed similar results when Piezo1 was removed from bone cells grown in the laboratory. Finally, Li et al. tested the impact of a chemical called Yoda1 on bones. Yoda1 makes the Piezo1 channel open, thus mimicking a physical force. These experiments showed that mice treated with Yoda1 had thicker bones than untreated mice. The ability of human bone to become stronger in response to exercise decreases with age, which contributes to the development of osteoporosis. Conditions that require severely restricted exercise, such as disability or extended bedrest, also lead to bone loss. These experiments show that Piezo1 allows bone to respond to physical force, and suggest Piezo1 as a promising therapeutic target to help curtail bone loss in these conditions.

The safety of microbial cultures utilized for consumption is vital for public health and should be thoroughly assessed. Although general aspects on the safety assessment of microbial cultures have been suggested, no methodological detail nor procedural guideline have been published. Herein, we propose a detailed protocol on microbial strain safety assessment via whole-genome sequence analysis. A starter culture employed in traditional fermented pork production, nham , namely Lactobacillus plantarum BCC9546, was used as an example. The strain’s whole-genome was sequenced through several next-generation sequencing techniques. Incomplete plasmid information from the PacBio sequencing platform and shorter chromosome size from the hybrid Oxford Nanopore-Illumina platform were noted. The methods for 1) unambiguous species identification using 16S rRNA gene and average nucleotide identity, 2) determination of virulence factors and undesirable genes, 3) determination of antimicrobial resistance properties and their possibility of transfer, and 4) determination of antimicrobial drug production capability of the strain were provided in detail. Applicability of the search tools and limitations of databases were discussed. Finally, a procedural guideline for the safety assessment of microbial strains via whole-genome analysis was proposed.

Several common oncogenic pathways have been implicated in the emergence of renowned metabolic features in cancer, which in turn are deemed essential for cancer proliferation and survival. However, the extent to which different cancers coordinate their metabolism to meet these requirements is largely unexplored. Here we show that even in the heterogeneity of metabolic regulation a distinct signature encompassed most cancers. On the other hand, clear cell renal cell carcinoma (ccRCC) strongly deviated in terms of metabolic gene expression changes, showing widespread down-regulation. We observed a metabolic shift that associates differential regulation of enzymes in one-carbon metabolism with high tumor stage and poor clinical outcome. A significant yet limited set of metabolic genes that explained the partial divergence of ccRCC metabolism correlated with loss of von Hippel-Lindau tumor suppressor (VHL) and a potential activation of signal transducer and activator of transcription 1. Further network-dependent analyses revealed unique defects in nucleotide, one-carbon, and glycerophospholipid metabolism at the transcript and protein level, which contrasts findings in other tumors. Notably, this behavior is recapitulated by recurrent loss of heterozygosity in multiple metabolic genes adjacent to VHL . This study therefore shows how loss of heterozygosity, hallmarked by VHL deletion in ccRCC, may uniquely shape tumor metabolism.

Loss of estrogens at menopause is a major cause of osteoporosis and increased fracture risk. Estrogens protect against bone loss by decreasing osteoclast number through direct actions on cells of the myeloid lineage. Here, we investigated the molecular mechanism of this effect. We report that 17β-estradiol (E 2 ) decreased osteoclast number by promoting the apoptosis of early osteoclast progenitors, but not mature osteoclasts. This effect was abrogated in cells lacking Bak/Bax—two pro-apoptotic members of the Bcl-2 family of proteins required for mitochondrial apoptotic death. FasL has been previously implicated in the pro-apoptotic actions of E 2 . However, we show herein that FasL-deficient mice lose bone mass following ovariectomy indistinguishably from FasL-intact controls, indicating that FasL is not a major contributor to the anti-osteoclastogenic actions of estrogens. Instead, using microarray analysis we have elucidated that ERα-mediated estrogen signaling in osteoclast progenitors decreases “oxidative phosphorylation” and the expression of mitochondria complex I genes. Additionally, E 2 decreased the activity of complex I and oxygen consumption rate. Similar to E 2 , the complex I inhibitor Rotenone decreased osteoclastogenesis by promoting osteoclast progenitor apoptosis via Bak/Bax. These findings demonstrate that estrogens decrease osteoclast number by attenuating respiration, and thereby, promoting mitochondrial apoptotic death of early osteoclast progenitors.

The intestinal epithelium separates us from the microbiota but also interacts with it and thus affects host immune status and physiology. Previous studies investigated microbiota-induced responses in the gut using intact tissues or unfractionated epithelial cells, thereby limiting conclusions about regional differences in the epithelium. Here, we sought to investigate microbiota-induced transcriptional responses in specific fractions of intestinal epithelial cells. To this end, we used microarray analysis of laser capture microdissection (LCM)-harvested ileal and colonic tip and crypt epithelial fractions from germ-free and conventionally raised mice and from mice during the time course of colonization. We found that about 10% of the host's transcriptome was microbially regulated, mainly including genes annotated with functions in immunity, cell proliferation, and metabolism. The microbial impact on host gene expression was highly site specific, as epithelial responses to the microbiota differed between cell fractions. Specific transcriptional regulators were enriched in each fraction. In general, the gut microbiota induced a more rapid response in the colon than in the ileum. Our study indicates that the microbiota engage different regulatory networks to alter host gene expression in a particular niche. Understanding host-microbiota interactions on a cellular level may facilitate signaling pathways that contribute to health and disease and thus provide new therapeutic strategies.

We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production.

Development of high throughput analytical methods has given physicians the potential access to extensive and patient-specific data sets, such as gene sequences, gene expression profiles or metabolite footprints. This opens for a new approach in health care, which is both personalized and based on system-level analysis. Genome-scale metabolic networks provide a mechanistic description of the relationships between different genes, which is valuable for the analysis and interpretation of large experimental data-sets. Here we describe the generation of genome-scale active metabolic networks for 69 different cell types and 16 cancer types using the INIT (Integrative Network Inference for Tissues) algorithm. The INIT algorithm uses cell type specific information about protein abundances contained in the Human Proteome Atlas as the main source of evidence. The generated models constitute the first step towards establishing a Human Metabolic Atlas, which will be a comprehensive description (accessible online) of the metabolism of different human cell types, and will allow for tissue-level and organism-level simulations in order to achieve a better understanding of complex diseases. A comparative analysis between the active metabolic networks of cancer types and healthy cell types allowed for identification of cancer-specific metabolic features that constitute generic potential drug targets for cancer treatment.

Unilateral eyestalk ablation in the female black tiger shrimp Penaeus monodon is commonly employed to induce ovarian maturation. However, the importance of complementing this practice with the provision of live feed supplement (such as polychaetes) has not been emphasized in previous studies. Indeed, it has been less emphasized that female broodstock must be fed with live feeds such as polychaetes for this practice to be effective. While the effects of eyestalk ablation have been thoroughly studied in various aspects, the synergistic effects of feeding with live feeds and the ablation have never been elucidated at a transcriptome-wide level. With recent advances in the next-generation sequencing platforms, it is now possible to investigate the effects of eyestalk ablation and live feeds at the transcriptomic levels. This study employed both short-read Illumina RNA sequencing and long-read Pacific Biosciences (PacBio) isoform sequencing (Iso-seq) to generate the first high-quality ovarian reference transcriptome in P . monodon . This novel assembly allowed us to dissect the effects of feeds and eyestalk ablation and reveal their synergistic effects at the transcriptomic level through the regulation of important genes involved in fatty acid regulation, energy production, and hormone-mediated oocyte maturation pathways. The synergistic effects between the polychaete feeding and the eyestalk ablation in the process of ovarian maturation in black tiger shrimp suggest that without having proper nutrients from the polychaetes, female broodstock might not be ready to develop its ovary. However, even with proper nutrients, the eyestalk ablation is still necessary to perhaps manipulate the female endocrine of the black tiger shrimp. These findings shed the light on molecular mechanisms and key molecular pathways that lead to successful ovarian maturation.

Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.

The human gut microbiome plays an influential role in maintaining human health and it is a potential target for prevention and treatment of disease. Genome-scale metabolic models (GEMs) can provide an increased understanding of the mechanisms behind the effects of diet, the genotype-phenotype relationship and microbial robustness. Here we reconstructed GEMs for three key species, ( Bacteroides thetaiotamicron , Eubacterium rectale and Methanobrevibacter smithii ) as relevant representatives of three main phyla in the human gut (Bacteroidetes, Firmicutes and Euryarchaeota). We simulated the interactions between these three bacteria in different combinations of gut ecosystems and compared the predictions with the experimental results obtained from colonization of germ free mice. Furthermore, we used our GEMs for analyzing the contribution of each species to the overall metabolism of the gut microbiota based on transcriptome data and demonstrated that these models can be used as a scaffold for understanding bacterial interactions in the gut.