Soil bacterial diversity is associated with human population density in urban greenspaces

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here by permission of American Chemical Society for personal use, not for redistribution. The definitive version was published in Environmental Science and Technology 52 (2018): 5115–5124, doi:10.1021/acs.est.7b06417.Urban greenspaces provide extensive ecosystem services, including pollutant remediation, water management, carbon maintenance, and nutrient cycling. However, while the urban soil microbiota underpin these services, we still have limited understanding of the factors that influence their distribution. We characterized soil bacterial communities from turf-grasses associated with urban parks, streets and residential sites across a major urban environment, including a gradient of human population density. Bacterial diversity was significantly positively correlated with the population density; and species diversity was greater in park and street soils, compared to residential soils. Population density and greenspace type also led to significant differences in the microbial community composition that was also significantly correlated with soil pH, moisture and texture. Co-occurrence network analysis revealed that microbial guilds in urban soils were well correlated. Abundant soil microbes in high density population areas had fewer interactions, while abundant bacteria in high moisture soils had more interactions. These results indicate the significant influence of changes in urban demographics and land-use on soil microbial communities. As urbanization is rapidly growing across the planet, it is important to improve our understanding of the consequences of urban zoning on the soil microbiota.This study is supported by the Earth Microbiome Project (http://www.earthmicrobiome.org/) and the China Scholarship Council (http://en.csc.edu.cn/).2019-04-0

Distinct biogeographic patterns for archaea, bacteria, and fungi along the vegetation gradient at the continental scale in Eastern China

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in mSystems 2 (2017): e00174-16, doi:10.1128/mSystems.00174-16.The natural forest ecosystem in Eastern China, from tropical forest to boreal forest, has declined due to cropland development during the last 300 years, yet little is known about the historical biogeographic patterns and driving processes for the major domains of microorganisms along this continental-scale natural vegetation gradient. We predicted the biogeographic patterns of soil archaeal, bacterial, and fungal communities across 110 natural forest sites along a transect across four vegetation zones in Eastern China. The distance decay relationships demonstrated the distinct biogeographic patterns of archaeal, bacterial, and fungal communities. While historical processes mainly influenced bacterial community variations, spatially autocorrelated environmental variables mainly influenced the fungal community. Archaea did not display a distance decay pattern along the vegetation gradient. Bacterial community diversity and structure were correlated with the ratio of acid oxalate-soluble Fe to free Fe oxides (Feo/Fed ratio). Fungal community diversity and structure were influenced by dissolved organic carbon (DOC) and free aluminum (Ald), respectively. The role of these environmental variables was confirmed by the correlations between dominant operational taxonomic units (OTUs) and edaphic variables. However, most of the dominant OTUs were not correlated with the major driving variables for the entire communities. These results demonstrate that soil archaea, bacteria, and fungi have different biogeographic patterns and driving processes along this continental-scale natural vegetation gradient, implying different community assembly mechanisms and ecological functions for archaea, bacteria, and fungi in soil ecosystems.This research was financially supported by the National Natural Science Foundation of China (grant number 41520104001), the 111 Project, and the Fundamental Research Funds for the Central Universities

Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019

Background: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input. Findings: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6–4.3) with a prevalence of 454.6 million cases (417.4–499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4–225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9–3.6) deaths. With 262.4 million (224.1–309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively. Interpretation: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries

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. FUNDING Bill & Melinda Gates Foundation

Genome-based comparative analyses of Antarctic and temperate species of Paenibacillus.

Antarctic soils represent a unique environment characterised by extremes of temperature, salinity, elevated UV radiation, low nutrient and low water content. Despite the harshness of this environment, members of 15 bacterial phyla have been identified in soils of the Ross Sea Region (RSR). However, the survival mechanisms and ecological roles of these phyla are largely unknown. The aim of this study was to investigate whether strains of Paenibacillus darwinianus owe their resilience to substantial genomic changes. For this, genome-based comparative analyses were performed on three P. darwinianus strains, isolated from gamma-irradiated RSR soils, together with nine temperate, soil-dwelling Paenibacillus spp. The genome of each strain was sequenced to over 1,000-fold coverage, then assembled into contigs totalling approximately 3 Mbp per genome. Based on the occurrence of essential, single-copy genes, genome completeness was estimated at approximately 88%. Genome analysis revealed between 3,043-3,091 protein-coding sequences (CDSs), primarily associated with two-component systems, sigma factors, transporters, sporulation and genes induced by cold-shock, oxidative and osmotic stresses. These comparative analyses provide an insight into the metabolic potential of P. darwinianus, revealing potential adaptive mechanisms for survival in Antarctic soils. However, a large proportion of these mechanisms were also identified in temperate Paenibacillus spp., suggesting that these mechanisms are beneficial for growth and survival in a range of soil environments. These analyses have also revealed that the P. darwinianus genomes contain significantly fewer CDSs and have a lower paralogous content. Notwithstanding the incompleteness of the assemblies, the large differences in genome sizes, determined by the number of genes in paralogous clusters and the CDS content, are indicative of genome content scaling. Finally, these sequences are a resource for further investigations into the expression of physiological attributes that enable survival under extreme conditions and selection processes that affect prokaryotic genome evolution

Network-guided genomic and metagenomic analysis of the faecal microbiota of the critically endangered kakapo

The kakapo is a critically endangered, herbivorous parrot endemic to New Zealand. The kakapo hindgut hosts a dense microbial community of low taxonomic diversity, typically dominated by Escherichia fergusonii, and has proven to be a remarkably stable ecosystem, displaying little variation in core membership over years of study. To elucidate mechanisms underlying this robustness, we performed 16S rRNA gene-based co-occurrence network analysis to identify potential interactions between E. fergusonii and the wider bacterial community. Genomic and metagenomic sequencing were employed to facilitate interpretation of potential interactions observed in the network. E. fergusonii maintained very few correlations with other members of the microbiota, and isolates possessed genes for the generation of energy from a wide range of carbohydrate sources, including plant fibres such as cellulose. We surmise that this dominant microorganism is abundant not due to ecological interaction with other members of the microbiota, but its ability to metabolise a wide range of nutrients in the gut. This research represents the first concerted effort to understand the functional roles of the kakapo microbiota, and leverages metagenomic data to contextualise co-occurrence patterns. By combining these two techniques we provide a means for studying the diversity-stability hypothesis in the context of bacterial ecosystems

Amino acid usage heatmap of temperate <i>Paenibacillus</i> spp. and <i>P. darwinianus</i> strains.

<p>Amino acid usage heatmap of temperate <i>Paenibacillus</i> spp. and <i>P. darwinianus</i> strains.</p

Comparison of gene content in temperate <i>Paenibacillus</i> spp. and <i>P. darwinianus</i> strains by COG categories.

<p>Comparison of gene content in temperate <i>Paenibacillus</i> spp. and <i>P. darwinianus</i> strains by COG categories.</p

Cold-shock induced genes identified in genomes of temperate <i>Paenibacillus</i> spp. and <i>P. darwinianus</i> strains.

<p>1, <i>P. darwinianus</i> Br; 2, <i>P. darwinianus</i> CE1; 3, <i>P. darwinianus</i> MB1; 4, <i>P. curdlanolyticus</i> YK9; 5, <i>P. mucilaginous</i> K02; 6, <i>P. polymyxa</i> SC2; 7, <i>P. daejeonensis</i> DSM 15491; 8, <i>P. terrigena</i> DSM 21567; 9, <i>P. panacisoli</i> DSM 21345; 10, <i>P. terrae</i> HPL-003; 11, <i>P. taiwanensis</i> DSM 18679; 12, <i>P. pinihumi</i> DSM 23905.</p><p>Numbers in each column represent copy numbers per genome. Locus tags for each copy number are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108009#pone.0108009.s012" target="_blank">Table S11</a>.</p><p>Cold-shock induced genes identified in genomes of temperate <i>Paenibacillus</i> spp. and <i>P. darwinianus</i> strains.</p

Effectiveness of self-management applications in improving clinical health outcomes and adherence among diabetic individuals in low and middle-income countries:a systematic review

INTRODUCTION: A variety of mobile health (mHealth) applications are available to monitor an individual’s health or lifestyle to make it convenient to access healthcare facilities at home. The usability of mHealth applications in controlling HbA1c (estimated average blood glucose) levels is unclear despite their increasing use. The burden of type 2 diabetes mellitus (T2DM) is high in low and middle-income countries (LMICs), with the highest burden in the Indian population. Our objective is to identify the effectiveness of mHealth applications in managing blood glucose levels of individuals with T2DM and to assess the impact of using mHealth applications in managing T2DM concerning health-promoting behaviour among the LMICs in the context of India. METHODS AND ANALYSIS: The electronic databases included for search are PubMed, Ovid Medline, EBSCO, CINAHL, Scopus, Web of Science and the Cochrane Central Register of Controlled Trials; additional sources of the search will be grey literature available on diabetes management websites and reference lists of included studies. Studies published in the English language in indexed and peer-reviewed sources will be considered. Studies reporting the effectiveness of mobile applications in the management of T2D in LMICs will be eligible for inclusion. The Population-Intervention-Comparison-Outcomes framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement 2021 will be used for reporting. Data analysis will be carried out using narrative synthesis, and a meta-analysis may be conducted if we come across homogenous data for the outcome. ETHICS AND DISSEMINATION: As this study is a systematic review, we will not be recruiting any participants for the study and hence will not require ethical approval. The study summary will be disseminated at a conference. PROSPERO REGISTRATION NUMBER: CRD42021245517