spatial and temporal dynamics
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Author(s):  
Swatabdi R. Kamal ◽  
Shreya Potukutchi ◽  
David J. Gelovani ◽  
Robin E. Bonomi ◽  
Srinivasu Kallakuri ◽  
...  

2022 ◽  
Vol 194 (2) ◽  
Author(s):  
Martina Soumastre ◽  
Juan Piccini ◽  
Lorena Rodríguez-Gallego ◽  
Leticia González ◽  
Laura Rodríguez-Graña ◽  
...  

2022 ◽  
Author(s):  
Zheng XU ◽  
Dalong Hu ◽  
Laurence Don Wai Luu ◽  
Sophie Octavia ◽  
Anthony D Keil ◽  
...  

Whooping cough (pertussis) is a highly contagious respiratory disease caused by the bacterium Bordetella pertussis. Despite high vaccine coverage, pertussis has re-emerged in many countries and caused two large epidemics in Australia since 2007. Here, we undertook a genomic and phylogeographic study of 385 Australian B. pertussis isolates collected from 2008 to 2017. The Australian B. pertussis population was found to be composed of mostly ptxP3 strains carrying different fim3 alleles, with ptxP3-fim3A genotype expanded far more than ptxP3-fim3B. Within the former, there were six co-circulating epidemic lineages (EL1 to EL6). The multiple ELs emerged, expanded, and then declined at different time points over the two epidemics, likely driven by immune selection from pertussis vaccination and natural infection in addition to local and global transmission events. Both hard and soft selective sweeps through vaccine selection pressures determined the current B. pertussis population dynamics. Relative risk analysis found that once a new B. pertussis lineage emerged, it was more likely to spread locally within the first 1.5 years. However, after 1.5 years, any new lineage was likely to expand to a wider region and became no longer spatially structured across the country. Phylogenetic analysis revealed the expansion of ptxP3 strains was also associated with replacement of the type III secretion system allele bscI1 with bscI3. This study advanced our understanding of the epidemic population structure and spatial and temporal dynamics of B. pertussis in a highly immunised population.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12274
Author(s):  
Sarah J. Tucker ◽  
Kelle C. Freel ◽  
Elizabeth A. Monaghan ◽  
Clarisse E. S. Sullivan ◽  
Oscar Ramfelt ◽  
...  

Surveys of microbial communities across transitions coupled with contextual measures of the environment provide a useful approach to dissect the factors determining distributions of microorganisms across ecological niches. Here, monthly time-series samples of surface seawater along a transect spanning the nearshore coastal environment within Kāneʻohe Bay on the island of Oʻahu, Hawaiʻi, and the adjacent offshore environment were collected to investigate the diversity and abundance of SAR11 marine bacteria (order Pelagibacterales) over a 2-year time period. Using 16S ribosomal RNA gene amplicon sequencing, the spatiotemporal distributions of major SAR11 subclades and exact amplicon sequence variants (ASVs) were evaluated. Seven of eight SAR11 subclades detected in this study showed distinct subclade distributions across the coastal to offshore environments. The SAR11 community was dominated by seven (of 106 total) SAR11 ASVs that made up an average of 77% of total SAR11. These seven ASVs spanned five different SAR11 subclades (Ia, Ib, IIa, IV, and Va), and were recovered from all samples collected from either the coastal environment, the offshore, or both. SAR11 ASVs were more often restricted spatially to coastal or offshore environments (64 of 106 ASVs) than they were shared among coastal, transition, and offshore environments (39 of 106 ASVs). Overall, offshore SAR11 communities contained a higher diversity of SAR11 ASVs than their nearshore counterparts, with the highest diversity within the little-studied subclade IIa. This study reveals ecological differentiation of SAR11 marine bacteria across a short physiochemical gradient, further increasing our understanding of how SAR11 genetic diversity partitions into distinct ecological units.


Author(s):  
Chhedi Lal Gupta ◽  
Ran Avidov ◽  
Karuppasamy Kattusamy ◽  
Ibrahim Saadi ◽  
Vempalli Sudharsan Varma ◽  
...  

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