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全生物群落城市主义:对城市蜂巢进行采样揭示城市宏基因组

Holobiont Urbanism: sampling urban beehives reveals cities' metagenomes.

作者信息

Hénaff Elizabeth, Najjar Devora, Perez Miguel, Flores Regina, Woebken Christopher, Mason Christopher E, Slavin Kevin

机构信息

NYU Tandon School of Engineering, Brooklyn, NY, USA.

Center for Urban Science and Progress, NYU, Brooklyn, NY, USA.

出版信息

Environ Microbiome. 2023 Mar 30;18(1):23. doi: 10.1186/s40793-023-00467-z.

DOI:10.1186/s40793-023-00467-z
PMID:36991491
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10060141/
Abstract

BACKGROUND

Over half of the world's population lives in urban areas with, according to the United Nations, nearly 70% expected to live in cities by 2050. Our cities are built by and for humans, but are also complex, adaptive biological systems involving a diversity of other living species. The majority of these species are invisible and constitute the city's microbiome. Our design decisions for the built environment shape these invisible populations, and as inhabitants we interact with them on a constant basis. A growing body of evidence shows us that human health and well-being are dependent on these interactions. Indeed, multicellular organisms owe meaningful aspects of their development and phenotype to interactions with the microorganisms-bacteria or fungi-with which they live in continual exchange and symbiosis. Therefore, it is meaningful to establish microbial maps of the cities we inhabit. While the processing and sequencing of environmental microbiome samples can be high-throughput, gathering samples is still labor and time intensive, and can require mobilizing large numbers of volunteers to get a snapshot of the microbial landscape of a city.

RESULTS

Here we postulate that honeybees may be effective collaborators in gathering samples of urban microbiota, as they forage daily within a 2-mile radius of their hive. We describe the results of a pilot study conducted with three rooftop beehives in Brooklyn, NY, where we evaluated the potential of various hive materials (honey, debris, hive swabs, bee bodies) to reveal information as to the surrounding metagenomic landscape, and where we conclude that the bee debris are the richest substrate. Based on these results, we profiled 4 additional cities through collected hive debris: Sydney, Melbourne, Venice and Tokyo. We show that each city displays a unique metagenomic profile as seen by honeybees. These profiles yield information relevant to hive health such as known bee symbionts and pathogens. Additionally, we show that this method can be used for human pathogen surveillance, with a proof-of-concept example in which we recover the majority of virulence factor genes for Rickettsia felis, a pathogen known to be responsible for "cat scratch fever".

CONCLUSIONS

We show that this method yields information relevant to hive health and human health, providing a strategy to monitor environmental microbiomes on a city scale. Here we present the results of this study, and discuss them in terms of architectural implications, as well as the potential of this method for epidemic surveillance.

摘要

背景

世界上超过一半的人口居住在城市地区,据联合国预计,到2050年,近70%的人口将居住在城市。我们的城市由人类建造并为人类所用,但也是复杂的、适应性的生物系统,涉及多种其他生物物种。这些物种中的大多数是看不见的,构成了城市的微生物群落。我们对建筑环境的设计决策塑造了这些不可见的种群,而作为居民,我们一直在与它们互动。越来越多的证据表明,人类的健康和福祉依赖于这些互动。事实上,多细胞生物的发育和表型的重要方面归功于与它们持续交换和共生的微生物(细菌或真菌)的相互作用。因此,绘制我们所居住城市的微生物图谱是有意义的。虽然环境微生物群落样本的处理和测序可以高通量进行,但收集样本仍然耗费人力和时间,并且可能需要动员大量志愿者才能获取城市微生物景观的快照。

结果

在这里,我们假设蜜蜂可能是收集城市微生物群样本的有效合作者,因为它们每天在蜂巢半径2英里范围内觅食。我们描述了在纽约布鲁克林的三个屋顶蜂箱进行的一项试点研究的结果,在那里我们评估了各种蜂巢材料(蜂蜜、碎片、蜂巢拭子、蜜蜂身体)揭示周围宏基因组景观信息的潜力,并得出结论,蜜蜂碎片是最丰富的底物。基于这些结果,我们通过收集的蜂巢碎片对另外4个城市进行了分析:悉尼、墨尔本、威尼斯和东京。我们表明,每个城市都呈现出蜜蜂所看到的独特宏基因组特征。这些特征产生了与蜂巢健康相关的信息,如已知的蜜蜂共生体和病原体。此外,我们表明这种方法可用于人类病原体监测,有一个概念验证示例,我们从中恢复了已知导致“猫抓热”的病原体费氏立克次体的大多数毒力因子基因。

结论

我们表明这种方法产生了与蜂巢健康和人类健康相关的信息,提供了一种在城市规模上监测环境微生物群落的策略。在这里,我们展示了这项研究的结果,并从建筑影响以及这种方法在疫情监测方面的潜力进行了讨论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1cd/10061797/2db313104a7c/40793_2023_467_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1cd/10061797/e264e62c7692/40793_2023_467_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1cd/10061797/2db313104a7c/40793_2023_467_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1cd/10061797/e264e62c7692/40793_2023_467_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1cd/10061797/2db313104a7c/40793_2023_467_Fig2_HTML.jpg

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