Bacterial Community Specification in PM2.5 in Different Seasons in Xinxiang, Central China

Abstract

In China, air pollution has become a significant environmental threat to human health in recent years. Airborne bacteria are critical constituents of microbial aerosols, which contain numerous pathogens. However, the effects of seasonal variations, environmental factors such as air pollution, and meteorological factors on microbial diversity are poorly understood. In this study, fine particulate matter (PM 2.5 ) samples (n = 12) were collected using a high-volume air sampler over 24-hour periods during all four seasons from April 2017 to January 2018. Concurrently, the average daily concentrations of various air pollutants and the meteorological conditions were monitored. High-throughput sequencing of 16s rRNA was then employed to profile PM 2.5 bacterial communities. The results showed that the bacterial communities varied significantly by season. Proteobacteria (35.5%), Firmicutes (23.0%), and Actinobacteria (16.2%) were the most abundant bacterial phyla in the PM 2.5 samples. At the genus level, the diversity of the bacterial communities was significantly correlated with the ozone (O 3 ) concentration (r = 0.920, p = 0.001) and air temperature (T) (r = 0.534, p = 0.023). The results of this study can be used as a reference by other bioaerosol research that focuses on the health effects of atmospheric particulate matter.

Bioaerosol Sources, Sampling Methods, and Major Categories: A Comprehensive Overview

“…For sequencing analyses, the V4 region of the 16s rRNA gene was amplified using 515F and 806R primers through PCR, before the high-throughput sequencing of 16s rRNA was conducted on the Ion S5™ XL platform. The bacterial communities were found to be dominated by Proteobacteria (35.5%), Firmicutes (23.0%), and Actinobacteria (16.2%) (Li et al, 2019a). After dust invasions in Shanghai, Cyanobacteria was found to have increased significantly in dust samples and is known to promote hepatotoxicity and tumors in humans (Rao et al, 2020).…”

Microbial Metagenome of Airborne Particulate Matter: Methodology, Characteristics, and Influencing Parameters

“…수율을 높일 수 있는 전처리 방법을 비교 연구하였다 [90]. [21,33,36,64,79]. 액체 포집면에 채취한 경우에는 고르게 잘 섞어주는 과 정이 전처리로 수행되었다 [36].…”

“…Pseudomonas [46,48,50,64], Streptophyta [49], Pseudolabrys [62], Clostridium [62], Planococcus [59], Kocuria [59,67], Thiobacillus [44], Paracoccus [67], Ochrobacterum [38], Lactococcus [38,68], Lactobacillus [38,64], Cupriavidus [38], Enhydrobacter [64], Staphylococcus [51], Thermus Proteobacteria와 Actinobacteria는 매우 건조하며 자외선 이 강한 환경에도 견딜 수 있기 때문에 [100], 대기오염이 악 화된 이후에도 감소하지 않고 오히려 환경에 적응한 후에 증가하였다 [66]. 대기오염이 심한 조건에서는 Bacillus, Sphingomonas, Rubellimicrobium 및 Kocuria 등의 우점도 가 높은데, 이들은 가혹한 환경에서 생존이 가능하기 때문으 로 추정된다 [51].…”

“…속 수준에서 미생물의 상대적 풍부함은 일 산화탄소 농도와 양의 상관관계가 있었고 [44], 이산화황 농 도와 AM 다양성 사이에도 양의 상관관계가 있었다 [44,67]. 이산화질소는 다른 대기환경 요인보다 세균 농도에 더 많은 영향을 미쳤다 [64]. 세균의 군집 구조에 미치는 이산화질소 의 영향은 거의 적었고, 유의미한 상관관계가 없었다 [44,64].…”

“…이산화질소는 다른 대기환경 요인보다 세균 농도에 더 많은 영향을 미쳤다 [64]. 세균의 군집 구조에 미치는 이산화질소 의 영향은 거의 적었고, 유의미한 상관관계가 없었다 [44,64]. 오존은 곰팡이의 종 풍부도와 다양성에 영향을 미치는 또 다 른 중요한 요소이다.…”