Using chemical structure and inocula characteristics to predictively model biodegradation rate

PhD ThesisPredictive biodegradation models [i.e. Quantitative Structure Biodegradation Relationship (QSBR) models] might be used as an alternative to current regulatory biodegradation tests to predict chemical persistence. Current models are mostly based on the results derived from regulatory Ready Biodegradability Tests (RBTs), which are highly variable and were not designed to provide half-life data and therefore fundamentally undermines efforts to reliably predict chemical persistence. Improvement to existing approaches for developing and verifying predictive models and their reliability, respectively, have been proposed, and the use of functional gene and 16S rRNA amplicon sequencing techniques towards identifying and quantifying the putative chemical degraders have been studied. Several QSBR models for aromatic chemicals were developed according to OECD principles. Models for mono-aromatic chemicals were verified and calibrated with experimentally determined rates (both from pure culture and natural mixed communities). Traditional test methods were combined with functional genes and 16S amplicon sequence analyses to develop a relationship between rate, chemical concentration and competent putative chemical degrader abundance. QSBR models for mono-aromatic chemicals were stable (R2 = 0.8924), robust (Q2LOO = 0.8718) and had good predictive ability (Q2F1 = 0.8829, Q2F2 = 0.8835, and Q2F3 = 0.9178). In these models, biodegradation rates were associated with electronic, lipophilic and steric descriptors, and thus provided information on the mechanisms of different rate-limiting steps associated with the biodegradation process. However, all the variation in biodegradation rates cannot be explained by the structure alone, the prevailing environmental conditions have a significant role in determining the extent of chemical degradation. Biodegradation rates (k) of chemicals in natural mixed communities were significantly correlated with the ratio of abundance of initial putative degrader abundances (X0) and the starting chemical concentration (C0) (Pearson correlation coefficient (r) > 0.9 and p-value < 0.05). Predictive models developed by relating k with X0 and C0 reliably predicted the rate of studied chemicals. Experimentally determined rates further formed the basis towards calibrating the developed QSBR models. The molecular analysis revealed that majority of identified putative chemical degraders were rare taxa, and their enrichment did not necessarily influence the overall biomass count of the microbial community, and therefore biodegradation models that only consider the overall biomass would not account for the kind of relationships found in this study. Application of 16S amplicon sequencing and functional gene analyses techniques in biodegradation studies will help in depth screening of diversity and function of microbial community in an inoculum and enables better understanding of biodegradation outcomes.funded by the Engineering and Physical Sciences Research Counci

The experimental determination of reliable biodegradation rates for mono-aromatics towards evaluating QSBR models

Quantitative Structure Biodegradation Relationships (QSBRs) are a tool to predict the biodegradability of chemicals. The objective of this work was to generate reliable biodegradation data for mono-aromatic chemicals in order to evaluate and verify previously developed QSBRs models. A robust biodegradation test method was developed to estimate specific substrate utilization rates, which were used as a proxy for biodegradation rates of chemicals in pure culture. Five representative mono-aromatic chemicals were selected that spanned a wide range of biodegradability. Aerobic biodegradation experiments were performed for each chemical in batch reactors seeded with known degraders. Chemical removal, degrader growth and CO2 production were monitored over time. Experimental data were interpreted using a full carbon mass balance model, and Monod kinetic parameters (Y, Ks, qmax and μmax) for each chemical were determined. In addition, stoichiometric equations for aerobic mineralization of the test chemicals were developed. The theoretically estimated biomass and CO2 yields were similar to those experimentally observed; 35 (s.d ± 8) of the recovered substrate carbon was converted to biomass, and 65 (s.d ± 8) was mineralised to CO2. Significant correlations were observed between the experimentally determined specific substrate utilization rates, as represented by qmax and qmax/Ks, at high and low substrate concentrations, respectively, and the first order biodegradation rate constants predicted by a previous QSBR study. Similarly, the correlation between qmax and selected molecular descriptors characterizing the chemicals structure in a previous QSBR study was also significant. These results suggest that QSBR models can be reliable and robust in prioritising chemical half-lives for regulatory screening purposes

A quantitative structure-biodegradation relationship (QSBR) approach to predict biodegradation rates of aromatic chemicals

The objective of this work was to develop a QSBR model for the prioritization of organic pollutants based on biodegradation rates from a database containing globally harmonized biodegradation tests using relevant molecular descriptors. To do this, we first categorized the chemicals into three groups (Group 1: simple aromatic chemicals with a single ring, Group 2: aromatic chemicals with multiple rings and Group3: Group 1 plus Group 2) based on molecular descriptors, estimated the first order biodegradation rate of the chemicals using rating values derived from the BIOWIN3 model, and finally developed, validated and defined the applicability domain of models for each group using a multiple linear regression approach. All the developed QSBR models complied with OECD principles for QSAR validation. The biodegradation rate in the models for the two groups (Group 2 and 3 chemicals) are associated with abstract molecular descriptors that provide little relevant practical information towards understanding the relationship between chemical structure and biodegradation rates. However, molecular descriptors associated with the QSBR model for Group 1 chemicals (R2 = 0.89, Q2loo = 0.87) provided information on properties that can readily be scrutinised and interpreted in relation to biodegradation processes. In combination, these results lead to the conclusion that QSBRs can be an alternative tool to estimate the persistence of chemicals, some of which can provide further insights into those factors affecting biodegradation

COVID-19-related knowledge, attitudes, and practices among adolescents and young people in Bihar and Uttar Pradesh, India: Study description

To control the spread of COVID-19 in India and to aid the efforts of the Ministry of Health and Family Welfare (MOHFW), the Population Council and other non-governmental organizations are conducting research to assess residents’ ability to follow sanitation and social distancing precautions under a countrywide lockdown. The Population Council COVID-19 study team is implementing rapid phone-based surveys to collect information on knowledge, attitudes and practices, as well as needs, among 2,041 young people (ages 19-23 years) and/or an adult household member, sampled from an existing prospective cohort study with a total sample size of 20,574 in Bihar (n=10,433) and Uttar Pradesh (n=10,141). Baseline was conducted from April 3-22; subsequent iterations of the survey are planned to be conducted on a monthly basis. Baseline findings on awareness of COVID-19 symptoms, perceived risk, awareness of and ability to carry out preventive behaviors, misconceptions, and fears will inform the development of government and other stakeholders’ interventions and/or strategies. We are committed to openly sharing the latest versions of the study description, questionnaires, deidentified or aggregated datasets, and preliminary results. Data and findings can also be shared with partners working in COVID-19 response

Fate of four Different Classes of Chemicals Under Aerobic and Anaerobic Conditions in Biological Wastewater Treatment

The removal mechanisms and extent of degradation of 28 chemicals (triclosan, fifteen polycyclic aromatic hydrocarbons, four estrogens, and eight polybrominated diphenyl ether congeners) in different biological treatment systems [activated sludge, up-flow anaerobic sludge blanket reactor (UASB) and waste stabilization pond (WSP)] was investigated to provide insights into the limits of engineered biological treatment systems. This was done through degradation experiments with inhibition and abiotic controls in static reactors under aerobic and anaerobic conditions. Estrogens showed higher first order degradation rates (0.1129 h−1) under aerobic conditions with activated sludge inocula followed by low molecular weight (LMW) PAHs (0.0171 h−1), triclosan (0.0072 h−1), middle (MMW) (0.0054 h−1) and high molecular weight PAHs (HMW) (0.0033 h−1). The same trend was observed under aerobic conditions with a facultative inoculum from a WSP, although at a much slower rate. Biodegradation was the major removal mechanism for these chemicals in the activated sludge and WSP WWTPs surveyed. Photodegradation of these chemicals was also observed and varied across the group of chemicals (estrogens (light rate = 0.4296 d−1; dark = 0.3900 d−1) degraded faster under light conditions while reverse was the case for triclosan (light rate = 0.0566 d−1; dark = 0.1752 d−1). Additionally, all the chemicals were resistant to anaerobic degradation with UASB sludge, which implies that their removal in the UASB of the surveyed WWTP was most likely via sorption onto solids. Importantly, the first order degradation rate determined in this study was used to estimate predicted effluent concentrations (PECs). The PECs showed good agreement with the measured effluent concentrations from a previous study for these treatment systems

A New Molecular Surveillance System for Leishmaniasis

Presently, global efforts are being made to control and eradicate the deadliest tropical diseases through the improvement of adequate interventions. A critical point for programs to succeed is the prompt and accurate diagnosis in endemic regions. Rapid diagnostic tests (RDTs) are being massively deployed and used to improve diagnosis in tropical countries. In the present report, we evaluated the hypothesis of, after use for diagnosis, the reuse of the Leishmania RDT kit as a DNA source, which can be used downstream as a molecular surveillance and/or quality control tool. As a proof of principle, a polymerase chain reaction-based method was used to detect Leishmania spp. minicircle kinetoplast DNA from leishmaniasis RDT kits. Our results show that Leishmania spp. DNA can be extracted from used RDTs and may constitute an important, reliable, and affordable tool to assist in future leishmaniasis molecular surveillance methods

Co-Circulation of Dengue Virus Serotypes 1, 2, and 3 during the 2022 Dengue Outbreak in Nepal: A Cross-Sectional Study

The largest dengue outbreak in the history of Nepal occurred in 2022, with a significant number of casualties. It affected all 77 districts, with the nation’s capital, Kathmandu (altitude 1300 m), being the hardest hit. However, the molecular epidemiology of this outbreak, including the dengue virus (DENV) serotype(s) responsible for this epidemic, remain unknown. Here, we report the epidemic trends, clinico-laboratory features, and virus serotypes and their viral load profiles that are associated with this outbreak in Nepal. Dengue-suspected febrile patients were investigated by routine laboratory, serological, and molecular tools, including a real-time quantitative polymerase chain reaction (qRT-PCR). Of the 538 dengue-suspected patients enrolled, 401 (74.5%) were diagnosed with dengue. Among these dengue cases, 129 (32.2%) patients who required hospital admission had significant associations with myalgia, rash, diarrhea, retro-orbital pain, bleeding, and abdominal pain. DENV-1, -2, and -3 were identified during the 2022 epidemic, with a predominance of DENV-1 (57.1%) and DENV-3 (32.1%), exhibiting a new serotype addition. We found that multiple serotypes circulated in 2022, with a higher frequency of hospitalizations, more severe dengue, and more deaths than in the past. Therefore, precise mapping of dengue and other related infections through integrated disease surveillance, evaluation of the dynamics of population-level immunity and virus evolution should be the urgent plans of action for evidence-based policy-making for dengue control and prevention in the country

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning