Emergence of methicillin resistance predates the clinical use of antibiotics

The discovery of antibiotics more than 80 years ago has led to considerable improvements in human and animal health. Although antibiotic resistance in environmental bacteria is ancient, resistance in human pathogens is thought to be a modern phenomenon that is driven by the clinical use of antibiotics(1). Here we show that particular lineages of methicillin-resistant Staphylococcus aureus-a notorious human pathogen-appeared in European hedgehogs in the pre-antibiotic era. Subsequently, these lineages spread within the local hedgehog populations and between hedgehogs and secondary hosts, including livestock and humans. We also demonstrate that the hedgehog dermatophyte Trichophyton erinacei produces two beta-lactam antibiotics that provide a natural selective environment in which methicillin-resistant S. aureus isolates have an advantage over susceptible isolates. Together, these results suggest that methicillin resistance emerged in the pre-antibiotic era as a co-evolutionary adaptation of S. aureus to the colonization of dermatophyte-infected hedgehogs. The evolution of clinically relevant antibiotic-resistance genes in wild animals and the connectivity of natural, agricultural and human ecosystems demonstrate that the use of a One Health approach is critical for our understanding and management of antibiotic resistance, which is one of the biggest threats to global health, food security and development

Emergence of methicillin resistance predates the clinical use of antibiotics.

The discovery of antibiotics more than 80 years ago has led to considerable improvements in human and animal health. Although antibiotic resistance in environmental bacteria is ancient, resistance in human pathogens is thought to be a modern phenomenon that is driven by the clinical use of antibiotics1. Here we show that particular lineages of methicillin-resistant Staphylococcus aureus-a notorious human pathogen-appeared in European hedgehogs in the pre-antibiotic era. Subsequently, these lineages spread within the local hedgehog populations and between hedgehogs and secondary hosts, including livestock and humans. We also demonstrate that the hedgehog dermatophyte Trichophyton erinacei produces two β-lactam antibiotics that provide a natural selective environment in which methicillin-resistant S. aureus isolates have an advantage over susceptible isolates. Together, these results suggest that methicillin resistance emerged in the pre-antibiotic era as a co-evolutionary adaptation of S. aureus to the colonization of dermatophyte-infected hedgehogs. The evolution of clinically relevant antibiotic-resistance genes in wild animals and the connectivity of natural, agricultural and human ecosystems demonstrate that the use of a One Health approach is critical for our understanding and management of antibiotic resistance, which is one of the biggest threats to global health, food security and development

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

EUCAST Ibrexafungerp MICs and Wild-Type Upper Limits for Contemporary Danish Yeast Isolates

Ibrexafungerp is a novel triterpenoid antifungal that inhibits glucan synthase and thus fungal cell wall synthesis. We examined the in vitro activity against contemporary clinical yeast, investigated inter-laboratory and intra-laboratory variability, suggested wild-type upper-limit values (WT-UL), and compared in vitro activity of ibrexafungerp to five licensed antifungals. Susceptibility to ibrexafungerp and comparators was investigated prospectively for 1965 isolates (11,790 MICs) and repetitively for three QC strains (1764 MICs) following the EUCAST E.Def 7.3.2 method. Elevated ibrexafungerp/echinocandin MICs prompted FKS sequencing. Published ibrexafungerp EUCAST MIC-distributions were retrieved and aggregated for WT-UL determinations following EUCAST principles. Ibrexafungerp MICs were ≤2 mg/L except against C. pararugosa, Cryptococcus and some rare yeasts. Modal MICs (mg/L) were 0.06/0.125/0.25/0.5/0.5/0.5/0.5/1/2 for C. albicans/C. dubliniensis/C. glabrata/C. krusei/C. parapsilosis/C. tropicalis/S. cerevisiae/C. guilliermondii/C. lusitaniae and aligned within ±1 dilution with published values. The MIC ranges for QC strains were: 0.06–0.25/0.5–1/0.125–0.5 for CNM-CL-F8555/ATCC6258/ATCC22019. The WT-UL (mg/L) were: 0.25/0.5/1/1/2 for C. albicans/C. glabrata/C. krusei/C. parapsilosis/C. tropicalis. Adopting these, non-wild-type rates were 0.3%/0.6%/0%/8%/3% for C. albicans/C. glabrata/C. krusei/C. parapsilosis/C. tropicalis and overall lower than for comparators except amphotericin B. Five/six non-wild-type C. albicans/C. glabrata were echinocandin and Fks non-wild-type (F641S, F659del or F659L). Eight C. parapsilosis and three C. tropicalis non-wild-type isolates were echinocandin and Fks wild-type. Partial inhibition near 50% in the supra-MIC range may explain variable MICs. Ibrexafungerp EUCAST MIC testing is robust, although the significance of paradoxical growth for some species requires further investigation. The spectrum is broad and will provide an oral option for the growing population with azole refractory infection

The fading boundaries between patient and environmental routes of triazole resistance selection in Aspergillus fumigatus

Aspergillus fumigatus is a saprobic fungus that may cause allergic syndromes, chronic pulmonary aspergillosis (CPA), and acute invasive aspergillosis (IA). Many patients suffering from aspergillus diseases benefit from antifungal therapy. Itraconazole, voriconazole, posaconazole, and isavuconazole have been shown to be the most effective compounds for prevention and treatment of the various aspergillus diseases. The use of alternative antifungal drugs, i.e., liposomal amphotericin B, is limited by toxicity and the echinocandins by fungistatic activity, while both also require intravenous access. As a consequence, the triazoles have become the recommended option for first-line therapy and chemoprophylaxis. Unfortunately, the effective use of triazoles has been threatened by the emergence of resistance in A. fumigatus. In voriconazole-treated patients, day 42 survival was 21% lower in voriconazole-resistant IA compared with voriconazole-susceptible infection. As the number of available drug classes is already very limited, some aspergillus diseases, such as central nervous system IA, are virtually untreatable if caused by a triazole-resistant isolate

In Vivo Selection of a Unique Tandem Repeat Mediated Azole Resistance Mechanism (TR120) in Aspergillus fumigatus cyp51A, Denmark

We report a fatal aspergillosis case in which STRAf typing and whole-genome sequencing substantiated in vivo emergence of an azole-resistant Aspergillus fumigatus with a 120-bp tandem repeat in the promoter region of cyp51A. This event, previously restricted to the environment, challenges current understanding of azole resistance development in A. fumigatus

Genotyping Reveals High Clonal Diversity and Widespread Genotypes of <i>Candida </i>Causing Candidemia at Distant Geographical Areas

The objectives of this study were to gain further insight on Candida genotype distribution and percentage of clustered isolates between hospitals and to identify potential clusters involving different hospitals and cities. We aim to genotype Candida spp. isolates causing candidemia in patients admitted to 16 hospitals in Spain, Italy, Denmark, and Brazil. Eight hundred and eighty-four isolates (Candida albicans, n = 534; C. parapsilosis, n = 282; and C. tropicalis, n = 68) were genotyped using species-specific microsatellite markers. CDC3, EF3, HIS3, CAI, CAIII, and CAVI were used for C. albicans, Ctrm1, Ctrm10, Ctrm12, Ctrm21, Ctrm24, and Ctrm28 for C. tropicalis, and CP1, CP4a, CP6, and B for C. parapsilosis. Genotypes were classified as singletons (genotype only found once) or clusters (same genotype infecting two or more patients). Clusters were defined as intra-hospital (involving patients admitted to a single hospital), intra-ward (involving patients admitted to the same hospital ward) or widespread (involving patients admitted to different hospitals). The percentage of clusters and the proportion of patients involved in clusters among species, genotypic diversity and distribution of genetic diversity were assessed. Seven hundred and twenty-three genotypes were detected, 78 (11%) being clusters, most of which (57.7%; n = 45/78) were intra-hospital clusters including intra-ward ones (42.2%; n = 19/45). The proportion of clusters was not statistically different between species, but the percentage of patients in clusters varied among hospitals. A number of genotypes (7.2%; 52/723) were widespread (found at different hospitals), comprising 66.7% (52/78) of clusters, and involved patients at hospitals in the same city (n = 21) or in different cities (n = 31). Only one C. parapsilosis cluster was a widespread genotype found in all four countries. Around 11% of C. albicans and C. parapsilosis isolates causing candidemia are clusters that may result from patient-to-patient transmission, widespread genotypes commonly found in unrelated patients, or insufficient microsatellite typing genetic discrimination