Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health

Rowney, Francis M.; Brennan, Georgina; Skjøth, C.; Griffith, Gareth; McInnes, Rachel N.; Clewlow, Yolanda; Adams‐Groom, Beverley; Barber, A.; Vere, Natasha de; Economou, Theo; Hegarty, Matthew J.; Hanlon, Helen M.; Jones, Laura; Kurganskiy, Alexander; Petch, Geoffrey; Potter, Caitlin; Rafiq, Abdullah Munawar; Warner, Amena; Wheeler, Benedict W.; Osborne, Nicholas; Creer, Simon

doi:10.1016/j.cub.2021.02.019

Cited by 25 publications

(16 citation statements)

References 38 publications

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“…Our study adds to the growing body of evidence that nuclear markers are well suited for quantitative molecular pollen research ( Banchi et al, 2020 ; Nunez et al, 2017 ; Richardson et al, 2021 ; Rowney et al, 2021 ). The correlation values for all taxa using trn L and nrITS2 in this study are very similar to those found in a recent study on bee-collected pollen quantification ( Richardson et al, 2021 ).…”

Section: Discussionmentioning

confidence: 64%

“…As an alternative to morphological pollen identification, DNA metabarcoding has been shown to provide increased taxonomic resolution and it has been used successfully on bee-collected pollen ( Bänsch et al, 2020 ; Elliott et al, 2021 ; Gous et al, 2021 ; Richardson et al, 2019 ) as well as airborne pollen ( Banchi et al, 2020 ; Brennan et al, 2019 ; Campbell et al, 2020 ; Kraaijeveld et al, 2015 ; Uetake et al, 2021 ). For grasses (Poaceae) for example, a recent study has shown that pollen of a small subset of all species present in the UK is likely to have a disproportionate influence on human health ( Rowney et al, 2021 ). However, such highly detailed information is not yet available for other plant families.…”

Section: Introductionmentioning

confidence: 99%

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DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring

Polling

Sin

Weger

et al. 2022

Science of The Total Environment

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Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trn L and nrITS2 provides highly improved taxonomic resolution for pollen from aerobiological samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families were detected, while using a microscope only 23 genera and 22 plant families were identified. NrITS2 produced almost double the number of OTUs and a much higher percentage of identifications to species level (80.1%) than trn L (27.6%). Furthermore, regressing relative read abundances against the relative abundances of microscopically obtained pollen concentrations showed a better correlation for nrITS2 (R 2 = 0.821) than for trn L (R 2 = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands ( Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that all three taxa were dominated by one or two species ( Alnus glutinosa/incana , Taxus baccata and Urtica dioica ). Highly allergenic as well as artificial hybrid species were found using nrITS2 that could not be identified using trn L or microscopic investigation ( Alnus × spaethii , Cupressus arizonica , Parietaria spp.). Furthermore, perMANOVA analysis indicated spatiotemporal patterns in airborne pollen trends that could be more clearly distinguished for all taxa using nrITS2 rather than trn L. All results indicate that nrITS2 should be the preferred marker of choice for molecular airborne pollen monitoring.

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Section: Discussionmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring

Polling

Sin

Weger

et al. 2022

Science of The Total Environment

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“…The model was increasingly used in various authoritative studies in different fields including ecology, biology, and human clinical research. 17 , 18 A novel model was adopted to analyze the relationship between the combination of muscle-fat and bone health in our study. In our study, the results of GAMs suggested that the relationship of fat and muscle on BMD was not one-way linear ( Figure 3 ).…”

Section: Discussionmentioning

confidence: 99%

Novel Insight into the Relationship Between Muscle-Fat and Bone in Type 2 Diabetes Ranging from Normal Weight to Obesity

Wang¹,

Peng²,

Zhang³

et al. 2022

DMSO

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Objective Decreased bone mineral density (BMD) is a common complication in individuals with type 2 diabetes mellitus (T2DM). Body weight, mainly consisting of muscle and fat, is the main determinant of BMD and fracture risks but does not accurately describe nutritional status. Most studies suggest that skeletal muscle mass (SMM) promotes BMD, while body fat mass (BFM) decreases BMD. However, the combined effect of SMM and BFM on BMD is elusive. Thus, the study aims to explore the combined effect of fat and muscle by the ratio index SMM/BFM on BMD in T2DM. Methods BFM and SMM were measured by the bioelectrical impedance analysis (BIA) method among 593 T2DM individuals ranging from normal weight and obesity. BMD was analyzed by DXA. Novel non-linear generalized additive models (GAMs) were used as the statistical analysis method. Results The results demonstrated that BMD T score/Z score of both femur and lumbar vertebrae were significantly higher and waist–hip ratio (WHR) was significantly lower in the high SMM/BFM group of both normal weight and overweight groups in T2DM individuals. Hence, SMM/BFM might be a good factor indicating BMD in different weight ranges. Additionally, the relationship between muscle fat and BMD was not linear. Notably, this correlation was not influenced by hyperglycemia in T2DM since different analytic models adjusted with the age, gender, BMI and HbA1c were adopted in this study. Furthermore, the impact of trunk fat (central, visceral fat most) and non-trunk fat (peripheral, the sum of subcutaneous limb fat most) on BMD was inconsistent. BMD presented unlimited reduction with trunk BFM increasing, while sustaining minimal diminishment with non-trunk BFM accumulation. Conclusion Our study provided a novel viewpoint relationship between muscle-fat and bone, and SMM/BFM might be a potential biomarker for bone health and clinical treatments of diabetes and related metabolic syndromes.

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“…While most research has focused on bacteria, microalgae (Tesson et al 2016) and fungi have also been explored (Fröhlich-Nowoisky et al 2012). Plant pollen is intensively studied for its allergenic potential and public health implications and metabarcoding is starting to be used for its identification (Kraaijeveld et al 2014; Brennan et al 2019; Rowney et al 2021). Fungal spores were targeted for biodiversity monitoring of the regional fungal community (Abrego et al 2018; 2020) and are currently being evaluated worldwide in the Global Spore Sampling Project (Ovaskainen et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Airborne environmental DNA metabarcoding for the monitoring of terrestrial insects - a proof of concept

Roger

Ghanavi

Danielsson

et al. 2021

Preprint

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Biodiversity is in decline due to human land use, exploitation, and climate change. To be able to counteract this alarming trend it is paramount to closely monitor biodiversity at global scales. Because this is practically impossible with traditional methods, the last decade has seen a strong push for solutions. In aquatic ecosystems the monitoring of species from environmental DNA (eDNA) has emerged as one of the most powerful tools at our disposal but in terrestrial ecosystems the power of eDNA for monitoring has so far been hampered by the local scale of the samples. In this study we report the first attempt to detect insects from airborne eDNA. We compare our results to two traditional insect monitoring projects (1) using light trapping for moth monitoring and (2) transect counts for the monitoring of butterflies and wild bees. While we failed to detect many of the same species monitored with the traditional methods, airborne eDNA metabarcoding revealed DNA from from six classes of Arthropods, and twelve order of Insects - including representatives from all of the four largest orders: Diptera (flies), Lepidoptera (butterflies and moths), Coleoptera (beetles) and Hymenoptera (bees, wasps and ants). We also recovered DNA from nine species of vertebrates, including frogs, birds and mammals as well as from 12 other phyla. We suggest that airborne eDNA has the potential to become a powerful tool for terrestrial biodiversity monitoring, with many impactful applications including the monitoring of pests, invasive or endangered species or disease vectors.

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Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health

Cited by 25 publications

References 38 publications

DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring

DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring

Novel Insight into the Relationship Between Muscle-Fat and Bone in Type 2 Diabetes Ranging from Normal Weight to Obesity

Airborne environmental DNA metabarcoding for the monitoring of terrestrial insects - a proof of concept

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