Ovine pedomics : the first study of the ovine foot 16S rRNA-based microbiome

We report the first study of the bacterial microbiome of ovine interdigital skin based on 16S rRNA by pyrosequencing and conventional cloning with Sanger-sequencing. Three flocks were selected, one a flock with no signs of footrot or interdigital dermatitis, a second flock with interdigital dermatitis alone and a third flock with both interdigital dermatitis and footrot. The sheep were classified as having either healthy interdigital skin (H), interdigital dermatitis (ID) or virulent footrot (VFR). The ovine interdigital skin bacterial community varied significantly by flock and clinical condition. The diversity and richness of operational taxonomic units was greater in tissue from sheep with ID than H or VFR affected sheep. Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria were the most abundant phyla comprising 25 genera. Peptostreptococcus, Corynebacterium and Staphylococcus were associated with H, ID and VFR respectively. Sequences of Dichelobacter nodosus, the causal agent of ovine footrot, were not amplified due to mismatches in the 16S rRNA universal forward primer (27F). A specific real time PCR assay was used to demonstrate the presence of D. nodosus which was detected in all samples including the flock with no signs of ID or VFR. Sheep with ID had significantly higher numbers of D. nodosus (104-109 cells/g tissue) than those with H or VFR feet

Functional Amyloids Composed of Phenol Soluble Modulins Stabilize Staphylococcus aureus Biofilms

Staphylococcus aureus is an opportunistic pathogen that colonizes the skin and mucosal surfaces of mammals. Persistent staphylococcal infections often involve surface-associated communities called biofilms. Here we report the discovery of a novel extracellular fibril structure that promotes S. aureus biofilm integrity. Biochemical and genetic analysis has revealed that these fibers have amyloid-like properties and consist of small peptides called phenol soluble modulins (PSMs). Mutants unable to produce PSMs were susceptible to biofilm disassembly by matrix degrading enzymes and mechanical stress. Previous work has associated PSMs with biofilm disassembly, and we present data showing that soluble PSM peptides disperse biofilms while polymerized peptides do not. This work suggests the PSMs' aggregation into amyloid fibers modulates their biological activity and role in biofilms

Medulloblastomas overexpress the p53-inactivating oncogene WIP1/PPM1D

Medulloblastoma is the most common malignant brain tumor of childhood. Despite numerous advances, clinical challenges range from recurrent and progressive disease to long-term toxicities in survivors. The lack of more effective, less toxic therapies results from our limited understanding of medulloblastoma growth. Although TP53 is the most commonly altered gene in cancers, it is rarely mutated in medulloblastoma. Accumulating evidence, however, indicates that TP53 pathways are disrupted in medulloblastoma. Wild-typep53-induced phosphatase 1 (WIP1 or PPM1D) encodes a negative regulator of p53. WIP1 amplification (17q22-q23) and its overexpression have been reported in diverse cancer types. We examined primary medulloblastoma specimens and cell lines, and detected WIP1 copy gain and amplification prevalent among but not exclusively in the tumors with 17q gain and isochromosome 17q (i17q), which are among the most common cytogenetic lesions in medulloblastoma. WIP1 RNA levels were significantly higher in the tumors with 17q gain or i17q. Immunoblots confirmed significant WIP1 protein in primary tumors, generally higher in those with 17q gain or i17q. Under basal growth conditions and in response to the chemotherapeutic agent, etoposide, WIP1 antagonized p53-mediated apoptosis in medulloblastoma cell lines. These results indicate that medulloblastoma express significant levels of WIP1 that modulate genotoxic responsiveness by negatively regulating p53

Comparative Genomics and Transcriptomics of Propionibacterium acnes

The anaerobic Gram-positive bacterium Propionibacterium acnes is a human skin commensal that is occasionally associated with inflammatory diseases. Recent work has indicated that evolutionary distinct lineages of P. acnes play etiologic roles in disease while others are associated with maintenance of skin homeostasis. To shed light on the molecular basis for differential strain properties, we carried out genomic and transcriptomic analysis of distinct P. acnes strains. We sequenced the genome of the P. acnes strain 266, a type I-1a strain. Comparative genome analysis of strain 266 and four other P. acnes strains revealed that overall genome plasticity is relatively low; however, a number of island-like genomic regions, encoding a variety of putative virulence-associated and fitness traits differ between phylotypes, as judged from PCR analysis of a collection of P. acnes strains. Comparative transcriptome analysis of strains KPA171202 (type I-2) and 266 during exponential growth revealed inter-strain differences in gene expression of transport systems and metabolic pathways. In addition, transcript levels of genes encoding possible virulence factors such as dermatan-sulphate adhesin, polyunsaturated fatty acid isomerase, iron acquisition protein HtaA and lipase GehA were upregulated in strain 266. We investigated differential gene expression during exponential and stationary growth phases. Genes encoding components of the energy-conserving respiratory chain as well as secreted and virulence-associated factors were transcribed during the exponential phase, while the stationary growth phase was characterized by upregulation of genes involved in stress responses and amino acid metabolism. Our data highlight the genomic basis for strain diversity and identify, for the first time, the actively transcribed part of the genome, underlining the important role growth status plays in the inflammation-inducing activity of P. acnes. We argue that the disease-causing potential of different P. acnes strains is not only determined by the phylotype-specific genome content but also by variable gene expression

Inactivation of Staphylococcal Phenol Soluble Modulins by Serum Lipoprotein Particles

Staphylococcus aureus virulence has been associated with the production of phenol soluble modulins (PSM). PSM are known to activate, attract and lyse neutrophils. However, the functional characterizations were generally performed in the absence of human serum. Here, we demonstrate that human serum can inhibit all the previously-described activities of PSM. We observed that serum can fully block both the cell lysis and FPR2 activation of neutrophils. We show a direct interaction between PSM and serum lipoproteins in human serum and whole blood. Subsequent analysis using purified high, low, and very low density lipoproteins (HDL, LDL, and VLDL) revealed that they indeed neutralize PSM. The lipoprotein HDL showed highest binding and antagonizing capacity for PSM. Furthermore, we show potential intracellular production of PSM by S. aureus upon phagocytosis by neutrophils, which opens a new area for exploration of the intracellular lytic capacity of PSM. Collectively, our data show that in a serum environment the function of PSM as important extracellular toxins should be reconsidered

Structural studies of thermally stable, combustion-resistant polymer composites

Composites of the industrially important polymer, poly(methyl methacrylate) (PMMA), were prepared by free-radical polymerization of MMA with varying amounts (1–30 wt. %) of sodium dioctylsulfosuccinate (Aerosol OT or AOT) surfactant added to the reaction mixture. The composites with AOT incorporated show enhanced resistance to thermal degradation compared to pure PMMA homopolymer, and micro-cone combustion calorimetry measurements also show that the composites are combustion-resistant. The physical properties of the polymers, particularly at low concentrations of surfactant, are not significantly modified by the incorporation of AOT, whereas the degradation is modified considerably for even the smallest concentration of AOT (1 wt. %). Structural analyses over very different lengthscales were performed. X-ray scattering was used to determine nm-scale structure, and scanning electron microscopy was used to determine μm-scale structure. Two self-assembled species were observed: large phase-separated regions of AOT using electron microscopy and regions of hexagonally packed rods of AOT using X-ray scattering. Therefore, the combustion resistance is observed whenever AOT self-assembles. These results demonstrate a promising method of physically incorporating a small organic molecule to obtain a highly thermally stable and combustion-resistant material without significantly changing the properties of the polymer

Defining motility in the Staphylococci

The ability of bacteria to move is critical for their survival in diverse environments and multiple ways have evolved to achieve this. Two forms of motility have recently been described for Staphylococcus aureus, an organism previously considered to be non-motile. One form is called spreading, which is a type of sliding motility and the second form involves comet formation, which has many observable characteristics associated with gliding motility. Darting motility has also been observed in Staphylococcus epidermidis. This review describes how motility is defined and how we distinguish between passive and active motility. We discuss the characteristics of the various forms of Staphylococci motility, the molecular mechanisms involved and the potential future research directions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere